{"as_of":"2026-08-09T06:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4b50a01349355e3f7e0a7739ba987be2cbba8c0549e23ff57c68189f2d5884dd","coverage":[{"denominator":95,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":95,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:11:40.585654Z","state":"measured"},{"denominator":113,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":113,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":18,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T00:38:15.328733Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T15:18:33.813982Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-08-05T14:37:25.598981Z","title":"Adversarial attacks on robotic vision language action models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.00117","last_updated":"2025-09-03T17:55:11Z","snapshot_observed_at":"2026-08-08T05:02:42.954294Z","submitted_at":"2025-08-28T17:59:07Z","title":"Embodied AI: Emerging Risks and Opportunities for Policy Action","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-05T14:37:25.598981Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2509.00117"},"observation_digest":"sha256:26d2a6116856b5a6cd881b6ad0efb7fc58ed8c1189dbfe0ce947c59d78a47ef2","observation_id":"56c4544d-d9f6-4201-b6e6-570b1e1f3fab","resolution":{"observed_at":"2026-08-05T14:37:25.598981Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2512.21815","last_updated":"2026-06-29T08:03:34Z","snapshot_observed_at":"2026-08-05T12:33:04.952799Z","submitted_at":"2025-12-26T01:01:25Z","title":"High-Entropy Tokens as Multimodal Failure Points in Vision-Language Models","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-16T19:29:43.382392Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2512.21815"},"observation_digest":"sha256:92cc1e0fb2998b6aa6eb13b1c81642e950b113effd1f0f24139c24b41849c102","observation_id":"d785a531-3760-4bc3-ab92-fe42c7835f4f","resolution":{"observed_at":"2026-05-16T19:31:13.125269Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-08-03T14:05:23.448332Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.21815","last_updated":"2026-06-29T08:03:34Z","snapshot_observed_at":"2026-08-05T12:33:04.952799Z","submitted_at":"2025-12-26T01:01:25Z","title":"High-Entropy Tokens as Multimodal Failure Points in Vision-Language Models","version":4},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T14:05:23.448332Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2512.21815"},"observation_digest":"sha256:e9a8d1ef844a663922520f0043fb431e065ae93f75d7ea47d8b40c2d32d099fe","observation_id":"f820d86b-5131-48c4-8b76-47580c354891","resolution":{"observed_at":"2026-08-03T14:05:23.448332Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-13T19:50:50.950451Z","title":"K., Robey, A., Zou, A., Ravichandran, Z., Pappas, G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.23117","last_updated":"2026-06-01T08:02:23Z","snapshot_observed_at":"2026-08-04T07:57:16.483761Z","submitted_at":"2026-03-24T12:14:12Z","title":"TRAP: Hijacking VLA CoT-Reasoning via Adversarial Patches","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-13T19:50:50.950451Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2603.23117"},"observation_digest":"sha256:9b819b594b97b74af2f8c40f075e03ee7bd5dcac87814f32cc1ec51cfa8cc681","observation_id":"0aec7b11-f324-47b0-a56b-7a2f3b0d881c","resolution":{"observed_at":"2026-07-13T19:50:50.950451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2603.24935","last_updated":"2026-04-07T10:20:22Z","snapshot_observed_at":"2026-08-06T10:57:09.113964Z","submitted_at":"2026-03-26T01:56:01Z","title":"SABER: A Stealthy Agentic Black-Box Attack Framework for Vision-Language-Action Models","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-15T01:06:42.421062Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2603.24935"},"observation_digest":"sha256:e2c57402948973f69d4dda592a2258a1bc5c45e85c7708d4b7c5c04c54046e7b","observation_id":"e7b3b776-b54d-43bf-a6dc-b989de00f8a8","resolution":{"observed_at":"2026-05-15T01:08:25.791834Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2604.03890","last_updated":"2026-04-04T23:06:16Z","snapshot_observed_at":"2026-07-06T22:52:57.182669Z","submitted_at":"2026-04-04T23:06:16Z","title":"From Prompt to Physical Action: Structured Backdoor Attacks on LLM-Mediated Robotic Control Systems","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-13T16:47:10.678447Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2604.03890"},"observation_digest":"sha256:e464a5a5167cc6ab077f921f18b2e5f0f58e4ca48fed2346223c373116081057","observation_id":"11d4d8ed-79e8-4493-a573-143f81210c60","resolution":{"observed_at":"2026-05-13T16:48:02.805576Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2604.09651","last_updated":"2026-03-30T03:54:04Z","snapshot_observed_at":"2026-08-07T01:26:00.994535Z","submitted_at":"2026-03-30T03:54:04Z","title":"FlowHijack: A Dynamics-Aware Backdoor Attack on Flow-Matching Vision-Language-Action Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-14T22:20:35.818770Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2604.09651"},"observation_digest":"sha256:3abf53642f6767cae5f8536b87d07eaf986a5042e4c8d59bdea31fc44a4c56ca","observation_id":"6137c7a4-a2d8-44b0-8bb8-6782d72cfe7a","resolution":{"observed_at":"2026-05-14T22:23:03.846995Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2604.23775","last_updated":"2026-04-26T15:58:19Z","snapshot_observed_at":"2026-07-06T23:09:58.193241Z","submitted_at":"2026-04-26T15:58:19Z","title":"Vision-Language-Action Safety: Threats, Challenges, Evaluations, and Mechanisms","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-08T05:56:13.913710Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2604.23775"},"observation_digest":"sha256:7d0ebfd304b8bf8017a4489baa35c709f4f92b508de3f34f8d00fba7e099b703","observation_id":"271e1474-c83c-4f4b-a890-278af2b8fe62","resolution":{"observed_at":"2026-05-11T21:21:10.586498Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2604.24790","last_updated":"2026-04-25T10:52:29Z","snapshot_observed_at":"2026-07-06T23:10:47.277692Z","submitted_at":"2026-04-25T10:52:29Z","title":"Semantic Denial of Service in LLM-controlled robots","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-08T07:59:42.478294Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2604.24790"},"observation_digest":"sha256:058952e5bf364e2e507d6db0bd07c3faf232c9c7d1ad7036b90a126e03180fd3","observation_id":"b1d9eb21-727b-4ae6-bdd8-48e5742cbda8","resolution":{"observed_at":"2026-05-11T20:46:14.626428Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2605.02900","last_updated":"2026-05-24T13:33:45Z","snapshot_observed_at":"2026-08-02T11:46:07.449862Z","submitted_at":"2026-03-28T13:21:44Z","title":"Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses","version":1},"reference_index":198,"source":"pdf_text","source_observed_at":"2026-05-14T22:20:31.623849Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2605.02900"},"observation_digest":"sha256:8af3e994ede93510c5a4f9e11a95c0a10a7594fe02b495c8c4289ffef5431c7f","observation_id":"9f5e4732-6c6d-4dc5-84e8-371556000c9e","resolution":{"observed_at":"2026-05-14T22:23:04.330888Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-13T17:08:58.831798Z","title":"Adversarial attacks on robotic vision language action models.arXiv preprint arXiv:2506.03350, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.02900","last_updated":"2026-05-24T13:33:45Z","snapshot_observed_at":"2026-08-02T11:46:07.449862Z","submitted_at":"2026-03-28T13:21:44Z","title":"Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses","version":2},"reference_index":164,"source":"pdf_text","source_observed_at":"2026-07-13T17:08:58.831798Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2605.02900"},"observation_digest":"sha256:1f583b35f0b833727515bc56e32b59448e252fd15ffbbee53ead1d5f6c1c9192","observation_id":"b4b5feba-993b-45df-b020-5bb525bb5b25","resolution":{"observed_at":"2026-07-13T17:08:58.831798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2605.29114","last_updated":"2026-05-27T21:21:37Z","snapshot_observed_at":"2026-07-06T23:38:37.178378Z","submitted_at":"2026-05-27T21:21:37Z","title":"ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-29T11:10:46.269185Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2605.29114"},"observation_digest":"sha256:cccb844e95feafb83686826cc2c6bf6ebe181d8092dce8532fb1711fb974b3b8","observation_id":"4270abea-ea1e-4112-97b3-b2edf3763d5c","resolution":{"observed_at":"2026-06-29T11:13:20.764580Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2606.11535","last_updated":"2026-06-10T00:37:03Z","snapshot_observed_at":"2026-08-07T11:12:52.147547Z","submitted_at":"2026-06-10T00:37:03Z","title":"Adversarial Attacks on Learned Policies for Surgical Robotic Tasks","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-27T10:07:43.624430Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2606.11535"},"observation_digest":"sha256:612751947d51deeab5305d722c6a5f12f2aac00103306cba6123ad9828bcba37","observation_id":"a8f39fb6-c78a-4773-b990-ce8864d880b8","resolution":{"observed_at":"2026-07-03T10:17:57.712107Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":"2506.03350","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-03T15:18:33.813982Z","title":"Pappas, Hamed Hassani, Matt Fredrikson, and J","venue":null,"work_id":"c5d1dae5-8ac6-407a-ad86-95fb7bfe3218","year":2025},"citing_paper":{"arxiv_id":"2606.12978","last_updated":"2026-06-11T07:12:17Z","snapshot_observed_at":"2026-08-03T00:41:34.363368Z","submitted_at":"2026-06-11T07:12:17Z","title":"Trajectory-Level Redirection Attacks on Vision-Language-Action Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T06:33:53.013076Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2606.12978"},"observation_digest":"sha256:013f93f8f8d60d21bdbf56fc06e921318cfe22620e4d76be59f9588304fbd624","observation_id":"14643cb9-ab5b-41b3-929e-b61651e4006e","resolution":{"observed_at":"2026-07-03T15:18:33.815886Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-07-31T14:03:37.094818Z","title":"Adversarial attacks on robotic vision language action models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.28226","last_updated":"2026-07-30T13:58:33Z","snapshot_observed_at":"2026-08-08T22:56:34.005518Z","submitted_at":"2026-07-30T13:58:33Z","title":"Security of World-Model-Based Embodied AI: A Lifecycle of Threats, Defenses, and Evaluation","version":1},"reference_index":110,"source":"pdf_text","source_observed_at":"2026-07-31T14:03:37.094818Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2607.28226"},"observation_digest":"sha256:cc1f11cd3ec52a29b1cca74012ff036b5ed5694e7041c18d537f2c513ddb3aab","observation_id":"4cf02cd1-f5a2-4b89-9fcb-fd4a0c1283e4","resolution":{"observed_at":"2026-07-31T14:03:37.094818Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-08-06T00:41:28.189227Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.01028","last_updated":"2026-08-02T06:06:28Z","snapshot_observed_at":"2026-08-07T17:25:43.376608Z","submitted_at":"2026-08-02T06:06:28Z","title":"VLAGuard: A Framework for Evaluating and Mitigating Physical Attention Hijacking in Vision-Language-Action Robots within Wireless Sensor Networks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T00:41:28.189227Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2608.01028"},"observation_digest":"sha256:589356c4a2a1372d5b906083cb968e528bac6fc67c5cfc4baae326bc82151af4","observation_id":"c623575b-7270-4968-8cbe-1d7c034a4973","resolution":{"observed_at":"2026-08-06T00:41:28.189227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-08-05T23:33:28.586419Z","title":"arXiv preprint arXiv:2506.03350 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.03207","last_updated":"2026-08-04T06:47:26Z","snapshot_observed_at":"2026-08-07T23:10:43.803857Z","submitted_at":"2026-08-04T06:47:26Z","title":"DRIFT: Derailing Denoising Trajectories of Flow-Matching VLAs with Adversarial Patch Attack","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-05T23:33:28.586419Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2608.03207"},"observation_digest":"sha256:ddb993c27254f05f703c6fccd5cff3aba78ee0f122896a38cc7b9ce38dc78678","observation_id":"d8894222-796d-4019-834d-cfedfc1712a5","resolution":{"observed_at":"2026-08-05T23:33:28.586419Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.03350","snapshot_observed_at":"2026-08-08T00:38:15.328733Z","title":"arXiv preprint arXiv:2506.03350 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05715","last_updated":"2026-08-06T07:52:55Z","snapshot_observed_at":"2026-08-09T05:11:35.577226Z","submitted_at":"2026-08-06T07:52:55Z","title":"Hijacking Robots with a Piece of Paper: A Systematic Study of Physical Prompt Injection in VLM-Controlled Robots","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-08T00:38:15.328733Z"},"links":{"cited_paper":"/paper/2506.03350","citing_paper":"/paper/2608.05715"},"observation_digest":"sha256:26d115905d92263f9b885b37181d577e80f2b2be3301f98a4116bd8e8f716876","observation_id":"3eb7074b-c81e-4cc4-b498-e7acc5d3c737","resolution":{"observed_at":"2026-08-08T00:38:15.328733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.03350/citation-record","integrity":"/paper/2506.03350/integrity","json":"/paper/2506.03350/citation-record.json","paper":"/paper/2506.03350"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.12998","last_updated":"2024-07-17T20:36:14Z","snapshot_observed_at":"2026-07-06T18:48:08.251086Z","submitted_at":"2024-07-17T20:36:14Z","title":"Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.12998","snapshot_observed_at":"2026-08-07T11:11:40.260798Z","title":"Surgical robot transformer (srt): Imitation learning for surgical tasks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.260798Z"},"links":{"cited_paper":"/paper/2407.12998","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:d6b6e1e85340037f675a6e8f30c23cb59a7372a14ba7ec67e4773bf7c7c7f541","observation_id":"e2638f25-9f56-45b6-b855-3f8482c90f3b","resolution":{"observed_at":"2026-08-07T11:11:40.260798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.264747Z","title":"General-purpose foundation models for increased autonomy in robot-assisted surgery.Nature Machine Intelligence, pages 1–9, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.264747Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:0aec5aebf12e55e7de1a22fdaeb520ce9050cec39c510b2be5c30bfa9e7b073f","observation_id":"0ed4bea1-ba5d-466b-8b89-6155f1232930","resolution":{"observed_at":"2026-08-07T11:11:40.264747Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08735","last_updated":"2024-07-11T17:59:22Z","snapshot_observed_at":"2026-07-06T18:45:01.801741Z","submitted_at":"2024-07-11T17:59:22Z","title":"Real-Time Anomaly Detection and Reactive Planning with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08735","snapshot_observed_at":"2026-08-07T11:11:40.268031Z","title":"Real-time anomaly detection and reactive planning with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.268031Z"},"links":{"cited_paper":"/paper/2407.08735","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:ba0cf22d7708d90dc8eb60445d0a6119603f64bc997a347d637381ee5f41e298","observation_id":"0d042e41-996c-40a5-8a96-c74ece747715","resolution":{"observed_at":"2026-08-07T11:11:40.268031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.271537Z","title":"Dolphins: Multimodal language model for driving","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.271537Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:8198469e1bb8b73a2397c61b1944a5a1d6d5f1a11bf6dba507062f8734077ec5","observation_id":"216ff483-159e-4104-945f-fd527514230b","resolution":{"observed_at":"2026-08-07T11:11:40.271537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06225","last_updated":"2023-10-12T17:06:17Z","snapshot_observed_at":"2026-08-08T06:37:20.511083Z","submitted_at":"2023-10-10T00:39:04Z","title":"GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models","version":2},"cited_work":{"arxiv_id":"2310.06225","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.06225","snapshot_observed_at":"2026-08-07T11:11:41.540821Z","title":"GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models","venue":"cs.AI","work_id":"a958d7a6-fa76-4c05-ba2f-3a89f5a06b02","year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.274805Z"},"links":{"cited_paper":"/paper/2310.06225","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:64d15d0848f699c9de2c5764dcd7b36e392477be5924b75fffeaf4a2c7ad44db","observation_id":"923b1969-c838-4021-8026-4f628b6de4be","resolution":{"observed_at":"2026-08-07T11:11:41.550160Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.279146Z","title":"Large language models can help boost food production, but be mindful of their risks.Frontiers in Artificial Intelligence, 7: 1326153, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.279146Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:3ce4c270e48f24e93f53fdf254338583df2f84b7831997aa1f3c725af2365daa","observation_id":"807cd2f2-78e2-4d0c-94a7-ae0358f52552","resolution":{"observed_at":"2026-08-07T11:11:40.279146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.283521Z","title":"Master plan","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.283521Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:6cc3b40329bf88924c6aaf6d02cb2427b59e118641606e5d09482de0b40120c6","observation_id":"fdcea2ce-bd8d-44ae-a516-318f872a4e76","resolution":{"observed_at":"2026-08-07T11:11:40.283521Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.288010Z","title":"Unitree go2","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.288010Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:9c88407645e15f554aad441ebde1fef3e86acb89cdaf4cefec1ada6d62c1c4f6","observation_id":"9e218c89-4030-44c4-af9a-5901d2ad0205","resolution":{"observed_at":"2026-08-07T11:11:40.288010Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24164","last_updated":"2026-01-08T17:01:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-31T17:22:30Z","title":"$\\pi_0$: A Vision-Language-Action Flow Model for General Robot Control","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.24164","snapshot_observed_at":"2026-08-07T11:11:40.294364Z","title":"π0: A vision-language-action flow model for general robot control, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.294364Z"},"links":{"cited_paper":"/paper/2410.24164","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:ec0820ec8bff20cca1429d62cb9b5aad768672aab47b41615349bad1cfd9c9a4","observation_id":"b849afe8-229e-477a-9709-267e2a35504b","resolution":{"observed_at":"2026-08-07T11:11:40.294364Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07775","last_updated":"2024-07-12T14:37:08Z","snapshot_observed_at":"2026-07-06T18:44:20.262496Z","submitted_at":"2024-07-10T15:49:07Z","title":"Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.07775","snapshot_observed_at":"2026-08-07T11:11:40.301692Z","title":"Mobility vla: Multimodal instruction navigation with long-context vlms and topological graphs.arXiv preprint arXiv:2407.07775, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.301692Z"},"links":{"cited_paper":"/paper/2407.07775","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:1fe53d386ce995e15e817b693f9f100224c4260f754163d840fb69f890101b45","observation_id":"5f28870d-87a9-47b5-aef3-fddf90adbc18","resolution":{"observed_at":"2026-08-07T11:11:40.301692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.304922Z","title":"Autort: Embodied foundation models for large scale orchestration of robotic agents.arXiv preprint arXiv:2401.12963, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.304922Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:fd4ac3e4cd5b0e688be9908c885aab0de7d2d8f3d29b0764612111c3e249b18c","observation_id":"aeef1849-75b8-4419-8cf8-576ad109c65c","resolution":{"observed_at":"2026-08-07T11:11:40.304922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.06942","last_updated":"2024-07-23T06:47:13Z","snapshot_observed_at":"2026-08-09T00:10:06.167600Z","submitted_at":"2023-12-12T02:34:06Z","title":"AI Control: Improving Safety Despite Intentional Subversion","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.06942","snapshot_observed_at":"2026-08-07T11:11:40.307636Z","title":"Ai control: Improving safety despite intentional subversion.arXiv preprint arXiv:2312.06942, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.307636Z"},"links":{"cited_paper":"/paper/2312.06942","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:6524940663f62420df55e3710ad9c80712909c8d84160441f127df543b5a3e3b","observation_id":"c75cd383-58c4-4964-8eca-3ea296dfcb39","resolution":{"observed_at":"2026-08-07T11:11:40.307636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14093","last_updated":"2024-12-20T02:22:19Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-18T17:41:24Z","title":"Alignment faking in large language models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14093","snapshot_observed_at":"2026-08-07T11:11:40.310964Z","title":"Alignment faking in large language models.arXiv preprint arXiv:2412.14093, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.310964Z"},"links":{"cited_paper":"/paper/2412.14093","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:1fe277e0d8e796f1e6a447dbc86dce67aefd2c38c57841ece97774de142f2863","observation_id":"2c9b4ea0-f4f4-4e86-938a-730a22d769cc","resolution":{"observed_at":"2026-08-07T11:11:40.310964Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14595","last_updated":"2024-07-01T19:58:00Z","snapshot_observed_at":"2026-07-06T18:34:29.513732Z","submitted_at":"2024-06-20T17:43:18Z","title":"Adversaries Can Misuse Combinations of Safe Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14595","snapshot_observed_at":"2026-08-07T11:11:40.314308Z","title":"Adversaries can misuse combinations of safe models.arXiv preprint arXiv:2406.14595, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.314308Z"},"links":{"cited_paper":"/paper/2406.14595","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:026293440cc72f35d55489740d94d55245b0c2f448e8b11af739f338a86bae3b","observation_id":"15125cb8-ae57-4f43-8ec1-8a7bf3d9eb45","resolution":{"observed_at":"2026-08-07T11:11:40.314308Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.317535Z","title":"Agentdojo: A dynamic environment to evaluate prompt injection attacks and defenses for llm agents","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.317535Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:83d091e309ab4ec776f0bf012d21b46308d70b5781c4ece2f334fc08785abe1c","observation_id":"239da7d6-d643-4676-b3fa-84a0c4a054ff","resolution":{"observed_at":"2026-08-07T11:11:40.317535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05499","last_updated":"2025-12-29T02:25:27Z","snapshot_observed_at":"2026-07-06T15:40:27.639368Z","submitted_at":"2023-06-08T18:43:11Z","title":"Prompt Injection attack against LLM-integrated Applications","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05499","snapshot_observed_at":"2026-08-07T11:11:40.321516Z","title":"Prompt injection attack against llm-integrated applications.arXiv preprint arXiv:2306.05499, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.321516Z"},"links":{"cited_paper":"/paper/2306.05499","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:153fdff00f265dd6df9763fc8c5be402b4fc39e476dc35df7df14d6f6ffa6692","observation_id":"627b5ad0-cdfa-4cd6-8663-ea090ef0c1c8","resolution":{"observed_at":"2026-08-07T11:11:40.321516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.18813","last_updated":"2025-06-24T08:05:33Z","snapshot_observed_at":"2026-08-07T19:59:01.081751Z","submitted_at":"2025-03-24T15:54:10Z","title":"Defeating Prompt Injections by Design","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.18813","snapshot_observed_at":"2026-08-07T11:11:40.324656Z","title":"Defeating prompt injections by design.arXiv preprint arXiv:2503.18813, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.324656Z"},"links":{"cited_paper":"/paper/2503.18813","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:2f344244ac2f95f36ba974fe86c687bf699899a3576d699ccf9249de4cfb73d1","observation_id":"5620d33d-b301-43fa-8769-f67b108b3bba","resolution":{"observed_at":"2026-08-07T11:11:40.324656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08419","last_updated":"2024-07-18T18:24:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-12T15:38:28Z","title":"Jailbreaking Black Box Large Language Models in Twenty Queries","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08419","snapshot_observed_at":"2026-08-07T11:11:40.327715Z","title":"Pappas, and Eric Wong","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.327715Z"},"links":{"cited_paper":"/paper/2310.08419","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:f931af31f6d819c74e11d975860889be9c6aaae4b673e2ae985b62cc4d47d22c","observation_id":"7032056c-c5ad-463d-80e0-340015449779","resolution":{"observed_at":"2026-08-07T11:11:40.327715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.15043","last_updated":"2023-12-20T20:48:57Z","snapshot_observed_at":"2026-07-06T15:59:23.019044Z","submitted_at":"2023-07-27T17:49:12Z","title":"Universal and Transferable Adversarial Attacks on Aligned Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.15043","snapshot_observed_at":"2026-08-07T11:11:40.330830Z","title":"Zico Kolter, and Matt Fredrikson","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.330830Z"},"links":{"cited_paper":"/paper/2307.15043","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:97a26e34c5bf5e5137fac7a33d01a2ae0deb75e90aec165602d074f5cf147844","observation_id":"15cc6568-1e5f-4cf0-9f70-c3905eea6629","resolution":{"observed_at":"2026-08-07T11:11:40.330830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.01318","last_updated":"2024-10-31T22:26:40Z","snapshot_observed_at":"2026-08-02T14:59:12.115203Z","submitted_at":"2024-03-28T02:44:02Z","title":"JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.01318","snapshot_observed_at":"2026-08-07T11:11:40.333890Z","title":"Jailbreakbench: An open robustness benchmark for jailbreaking large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.333890Z"},"links":{"cited_paper":"/paper/2404.01318","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:8bf84045505aa10a9cecb0756d589afa89dfe0c3a725997e27630ffe8908d3aa","observation_id":"a04a7ecb-8456-4aae-89f4-caa07a960682","resolution":{"observed_at":"2026-08-07T11:11:40.333890Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.13353","last_updated":"2024-08-13T07:19:59Z","snapshot_observed_at":"2026-08-07T20:44:37.002212Z","submitted_at":"2022-06-16T17:58:47Z","title":"Is Power-Seeking AI an Existential Risk?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.13353","snapshot_observed_at":"2026-08-07T11:11:40.338107Z","title":"Is power-seeking ai an existential risk?arXiv preprint arXiv:2206.13353,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.338107Z"},"links":{"cited_paper":"/paper/2206.13353","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:000676727db23d16f961013826cc1576ef79f23eb19af4c072bf15ddfd3ed8bf","observation_id":"9ed4e4c6-625a-4d4c-9959-08a987e02d8b","resolution":{"observed_at":"2026-08-07T11:11:40.338107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.01820","last_updated":"2021-12-01T11:22:52Z","snapshot_observed_at":"2026-08-01T23:32:03.638122Z","submitted_at":"2019-06-05T04:43:25Z","title":"Risks from Learned Optimization in Advanced Machine Learning Systems","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.01820","snapshot_observed_at":"2026-08-07T11:11:40.341689Z","title":"Risks from learned optimization in advanced machine learning systems.arXiv preprint arXiv:1906.01820, 2019","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.341689Z"},"links":{"cited_paper":"/paper/1906.01820","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:cf181d7685be81629ec6140aad60cdd3f607be769e7d7fb5a004d13ae352af34","observation_id":"95933152-0f97-4195-a734-497d345c0a15","resolution":{"observed_at":"2026-08-07T11:11:40.341689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10569","last_updated":"2023-07-26T03:57:03Z","snapshot_observed_at":"2026-07-06T15:56:15.361460Z","submitted_at":"2023-07-20T04:14:09Z","title":"Deceptive Alignment Monitoring","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10569","snapshot_observed_at":"2026-08-07T11:11:40.345067Z","title":"Deceptive alignment monitoring.arXiv preprint arXiv:2307.10569, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.345067Z"},"links":{"cited_paper":"/paper/2307.10569","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:85c494e4ac59bc57eea7f2dff4eca8d83ca2000bd9aa0d12b90d5f5a6cd2a344","observation_id":"b1007874-5152-4618-bab8-ab684268a9b2","resolution":{"observed_at":"2026-08-07T11:11:40.345067Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18565","last_updated":"2025-05-05T20:52:36Z","snapshot_observed_at":"2026-08-07T16:00:36.504782Z","submitted_at":"2025-04-21T11:39:22Z","title":"RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.18565","snapshot_observed_at":"2026-08-07T11:11:40.348373Z","title":"Replibench: Evaluating the autonomous replication capabilities of language model agents.arXiv preprint arXiv:2504.18565,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.348373Z"},"links":{"cited_paper":"/paper/2504.18565","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:eeca2480ff646a21510500107346f6a7fb74c0b1ae4737b34be2a9f342b1276e","observation_id":"fa19d45b-42b9-4813-a6bc-984737b7cbcb","resolution":{"observed_at":"2026-08-07T11:11:40.348373Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12140","last_updated":"2024-12-09T15:01:37Z","snapshot_observed_at":"2026-08-06T10:04:05.646150Z","submitted_at":"2024-12-09T15:01:37Z","title":"Frontier AI systems have surpassed the self-replicating red line","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.12140","snapshot_observed_at":"2026-08-07T11:11:40.351607Z","title":"Frontier ai systems have surpassed the self-replicating red line.arXiv preprint arXiv:2412.12140, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.351607Z"},"links":{"cited_paper":"/paper/2412.12140","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:ab57b8079ab40446fd84ff389a0744bf7097d25a6e1dc49c7e9f43b604c94129","observation_id":"826b1a83-6390-40fe-a2cf-1acf2962ef68","resolution":{"observed_at":"2026-08-07T11:11:40.351607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.09246","last_updated":"2024-09-05T19:46:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-13T15:46:55Z","title":"OpenVLA: An Open-Source Vision-Language-Action Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.09246","snapshot_observed_at":"2026-08-07T11:11:40.354837Z","title":"Openvla: An open-source vision-language-action model.arXiv preprint arXiv:2406.09246,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.354837Z"},"links":{"cited_paper":"/paper/2406.09246","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:ceeaabd35c46f11072c3c18e3a896aa9e17e6ce731dde3881b090586dc6223e3","observation_id":"fbeca933-5ef0-4c09-a27d-b0aab4da468c","resolution":{"observed_at":"2026-08-07T11:11:40.354837Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13691","last_updated":"2024-11-09T20:00:07Z","snapshot_observed_at":"2026-07-06T19:35:26.421419Z","submitted_at":"2024-10-17T15:55:36Z","title":"Jailbreaking LLM-Controlled Robots","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13691","snapshot_observed_at":"2026-08-07T11:11:40.362352Z","title":"Jailbreaking llm-controlled robots.arXiv preprint arXiv:2410.13691, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.362352Z"},"links":{"cited_paper":"/paper/2410.13691","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:e2b171b79a9d4e821ffc4b25f5a56e107cadd3a0f8de83a00d2abda0da8d78c9","observation_id":"ff9f4791-6992-44c6-ac4d-f862331dac1a","resolution":{"observed_at":"2026-08-07T11:11:40.362352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.20242","last_updated":"2026-06-09T05:19:18Z","snapshot_observed_at":"2026-07-06T18:53:31.241776Z","submitted_at":"2024-07-16T13:13:16Z","title":"BadRobot: Jailbreaking Embodied LLM Agents in the Physical World","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.20242","snapshot_observed_at":"2026-08-07T11:11:40.366090Z","title":"Badrobot: Manipulating embodied llms in the physical world.arXiv preprint arXiv:2407.20242, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.366090Z"},"links":{"cited_paper":"/paper/2407.20242","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:90df557b6dc2c364a0282ed56d87918f4e54c58a65faf635ed1c705b15a66223","observation_id":"60a2b6a8-73f4-4b1e-81fe-9fa461df6dbb","resolution":{"observed_at":"2026-08-07T11:11:40.366090Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.369464Z","title":"Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.369464Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:d6bf4550bfc82061870bfbaeb4011d98e2e572fc19c43046a158bcd6f9eb09f8","observation_id":"dc736ca6-a9ab-48f1-b599-11ffec3ed84c","resolution":{"observed_at":"2026-08-07T11:11:40.369464Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1504.00702","last_updated":"2016-04-19T01:33:13Z","snapshot_observed_at":"2026-08-09T02:12:37.186250Z","submitted_at":"2015-04-02T22:23:51Z","title":"End-to-End Training of Deep Visuomotor Policies","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1504.00702","snapshot_observed_at":"2026-08-07T11:11:40.372910Z","title":"End-to-end training of deep visuomotor policies, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.372910Z"},"links":{"cited_paper":"/paper/1504.00702","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:4b565d62c883b412f69cc27165f8f0b0d6210fab39534a3a1aa56e23f9dea168","observation_id":"ff4cf46c-6222-420c-8f09-37e79d8e7e0a","resolution":{"observed_at":"2026-08-07T11:11:40.372910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.12601","last_updated":"2022-11-18T05:57:09Z","snapshot_observed_at":"2026-08-02T11:48:59.131827Z","submitted_at":"2022-03-23T17:55:09Z","title":"R3M: A Universal Visual Representation for Robot Manipulation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.12601","snapshot_observed_at":"2026-08-07T11:11:40.376578Z","title":"R3m: A universal visual representation for robot manipulation, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.376578Z"},"links":{"cited_paper":"/paper/2203.12601","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:2a1e5043a085b3d7b060ede42e87da7ea3740413960a030d350e7c43602a9899","observation_id":"a7fe9501-ed00-4812-91cc-c61a19391ff4","resolution":{"observed_at":"2026-08-07T11:11:40.376578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.379677Z","title":"Attention is all you need.Advances in Neural Information Processing Systems, 30, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.379677Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:df5d9df98ac0b8039bf2a1cbd80ce97f6bf4fb56f7ef46c6889af40b1b11846d","observation_id":"64958992-f9da-4280-83fc-1fd88992192d","resolution":{"observed_at":"2026-08-07T11:11:40.379677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.17582","last_updated":"2023-07-19T19:30:28Z","snapshot_observed_at":"2026-08-06T07:22:36.341628Z","submitted_at":"2023-02-20T06:39:06Z","title":"ChatGPT for Robotics: Design Principles and Model Abilities","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.17582","snapshot_observed_at":"2026-08-07T11:11:40.383134Z","title":"Chatgpt for robotics: Design principles and model abilities, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.383134Z"},"links":{"cited_paper":"/paper/2306.17582","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:733888fa1116148848ce10f25f6194f8e80ef7920bf05a03bdc9146f9a2a6b4a","observation_id":"ed30fb58-ae09-437d-88f1-54a29a92197e","resolution":{"observed_at":"2026-08-07T11:11:40.383134Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.386287Z","title":"Code as policies: Language model programs for embodied control","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.386287Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:386e2300b5d03eaae5a5e178fde5f7289848a7ffd8765488beae4af49aa75c1b","observation_id":"f9a246e9-9350-46d2-ab56-99c0ae7dac44","resolution":{"observed_at":"2026-08-07T11:11:40.386287Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.389639Z","title":"How to prompt your robot: A promptbook for manipulation skills with code as policies","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.389639Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:5f6446a7b6edf57345f85176e44f90eac7a4f0e5920e2dab02ccb6b8ac67d89b","observation_id":"ed74ab90-1e54-4a0b-96a9-175150c9720d","resolution":{"observed_at":"2026-08-07T11:11:40.389639Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.392918Z","title":"Chatgpt for robotics: Design principles and model abilities.IEEE Access, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.392918Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:36e59565393ad50a5198a4644938508d4e79901165ec721944964301c05d2847","observation_id":"97a6686b-e2bc-4fae-a4a7-c505ef5d0344","resolution":{"observed_at":"2026-08-07T11:11:40.392918Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05932","last_updated":"2024-04-10T23:29:18Z","snapshot_observed_at":"2026-07-06T17:27:37.212340Z","submitted_at":"2024-02-08T18:59:03Z","title":"Driving Everywhere with Large Language Model Policy Adaptation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05932","snapshot_observed_at":"2026-08-07T11:11:40.396219Z","title":"Driving everywhere with large language model policy adaptation, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.396219Z"},"links":{"cited_paper":"/paper/2402.05932","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:2687c69ffa8b6c6610c62e305911eedf193c0610ce3466fd6741511321ae8f69","observation_id":"ae916383-166f-43d2-b1cc-f7be2bc7b023","resolution":{"observed_at":"2026-08-07T11:11:40.396219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12320","last_updated":"2023-11-21T03:32:01Z","snapshot_observed_at":"2026-08-06T10:43:26.992373Z","submitted_at":"2023-11-21T03:32:01Z","title":"A Survey on Multimodal Large Language Models for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12320","snapshot_observed_at":"2026-08-07T11:11:40.399503Z","title":"A survey on multimodal large language models for autonomous driving, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.399503Z"},"links":{"cited_paper":"/paper/2311.12320","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:96dbd060ac10e32fb2a680f1fb94073b4e6dbf1a3a48f8b8d0a588fca98555e7","observation_id":"fe66ef49-e91d-4a3b-9f6f-139d43a6edce","resolution":{"observed_at":"2026-08-07T11:11:40.399503Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2024.33600","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:41.126692Z","title":"Deploying and evaluating llms to program service mobile robots.IEEE Robotics and Automation Letters, 9(3):2853–2860, March 2024","venue":null,"work_id":"495ba5c6-d2e5-45f7-b2ab-8514be6c8b0f","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.403344Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:b5198d623cd0a759fdc76437913c411540ac2410d04e204ca2ce709bc1fc0c07","observation_id":"5ea615c3-fa3b-4d4e-a69f-a9ace6959a2a","resolution":{"observed_at":"2026-08-07T11:11:41.134751Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.406294Z","title":"SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Task Planning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.406294Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:ff88b2da8a8567964badb059421c4721f556bd07d8ac8652bb26287667b116ab","observation_id":"111d9616-9573-4ba0-8012-40f4128e90dc","resolution":{"observed_at":"2026-08-07T11:11:40.406294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.409342Z","title":"Palm: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240): 1–113, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.409342Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:a5bf3a9425c824388d03802acaaec220230c29c67b1c299b47d89d56a7be419f","observation_id":"bbcfb905-0bb3-41db-b88e-b94ea0a40760","resolution":{"observed_at":"2026-08-07T11:11:40.409342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.05442","last_updated":"2023-02-10T18:58:21Z","snapshot_observed_at":"2026-08-04T12:07:24.626442Z","submitted_at":"2023-02-10T18:58:21Z","title":"Scaling Vision Transformers to 22 Billion Parameters","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.05442","snapshot_observed_at":"2026-08-07T11:11:40.412772Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.412772Z"},"links":{"cited_paper":"/paper/2302.05442","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:7b0d88bcafce1ebda674fdc900921518d5a3728906cfcfe2174e6d5c0f52d73f","observation_id":"7d02eae8-43dc-4400-8256-542870d7463b","resolution":{"observed_at":"2026-08-07T11:11:40.412772Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.03378","last_updated":"2023-03-06T18:58:06Z","snapshot_observed_at":"2026-08-08T22:04:13.117781Z","submitted_at":"2023-03-06T18:58:06Z","title":"PaLM-E: An Embodied Multimodal Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.03378","snapshot_observed_at":"2026-08-07T11:11:40.415933Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.415933Z"},"links":{"cited_paper":"/paper/2303.03378","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:bb9ab736fe3d8dff9201467640bdfa20dbf37713dc10570fdc2b8cd877ba3dad","observation_id":"c02606e4-4990-47a7-941b-403485f46814","resolution":{"observed_at":"2026-08-07T11:11:40.415933Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.06135","last_updated":"2023-09-27T23:17:28Z","snapshot_observed_at":"2026-07-06T15:53:11.310262Z","submitted_at":"2023-07-12T12:37:55Z","title":"SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.06135","snapshot_observed_at":"2026-08-07T11:11:40.419092Z","title":"Sayplan: Grounding large language models using 3d scene graphs for scalable robot task planning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.419092Z"},"links":{"cited_paper":"/paper/2307.06135","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:c600bf84bb114e1239c593f5b4257543334efc1314b998a17617b62b3be133df","observation_id":"de04ff54-09b2-4422-a018-6f585975f8e8","resolution":{"observed_at":"2026-08-07T11:11:40.419092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.422422Z","title":"Tenenbaum, Antonio Torralba, Florian Shkurti, and Liam Paull","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.422422Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:33da8d989192b8b3dd85f02cbc2ddc9de146401b58e9fcc75424c999918f35bf","observation_id":"5d9b344b-c9f6-4d16-81e2-297627a67e6d","resolution":{"observed_at":"2026-08-07T11:11:40.422422Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.425459Z","title":"An embodied generalist agent in 3d world,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.425459Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:23e6bb7c8d71589673faf252258bc3fb1fd78ab9ad70f61ea37695c05cf79480","observation_id":"454e0696-c079-4d0e-909f-a5b833d1a46b","resolution":{"observed_at":"2026-08-07T11:11:40.425459Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.01691","last_updated":"2022-08-16T16:06:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-04T17:57:11Z","title":"Do As I Can, Not As I Say: Grounding Language in Robotic Affordances","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.01691","snapshot_observed_at":"2026-08-07T11:11:40.431994Z","title":"Do as i can and not as i say: Grounding language in robotic affordances","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.431994Z"},"links":{"cited_paper":"/paper/2204.01691","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:deba29216d40aaf972f76f949e03a9f596a504c4bc01ae4d203eef4968bd21fd","observation_id":"e366fbbc-a98d-45d6-a9fd-282cfbe72334","resolution":{"observed_at":"2026-08-07T11:11:40.431994Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:43.050983Z","title":"Octo: An open-source generalist robot policy","venue":null,"work_id":"060854b0-c5a4-4205-bd5c-6360b9490068","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.435203Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:3957065a37bde402a5a7a70b014665ddf0620d706e76cf4d31dec753f87d96eb","observation_id":"69f8b978-f345-4e2d-8ad3-13de2d76af9b","resolution":{"observed_at":"2026-08-07T11:11:43.107063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.15818","last_updated":"2023-07-28T21:18:02Z","snapshot_observed_at":"2026-08-02T16:17:50.621617Z","submitted_at":"2023-07-28T21:18:02Z","title":"RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.15818","snapshot_observed_at":"2026-08-07T11:11:40.438695Z","title":"Rt-2: Vision-language-action models transfer web knowledge to robotic control, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.438695Z"},"links":{"cited_paper":"/paper/2307.15818","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:e581b575d26b28639778da56579e1f14e86748299bbd92c20672e9ca53193c28","observation_id":"8f7cc1a5-e099-48d0-a700-894ab31e8269","resolution":{"observed_at":"2026-08-07T11:11:40.438695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08864","last_updated":"2025-05-14T15:22:36Z","snapshot_observed_at":"2026-08-08T01:53:43.555672Z","submitted_at":"2023-10-13T05:20:40Z","title":"Open X-Embodiment: Robotic Learning Datasets and RT-X Models","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08864","snapshot_observed_at":"2026-08-07T11:11:40.441575Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.441575Z"},"links":{"cited_paper":"/paper/2310.08864","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:07cb77cb64b693957a5fdabc03be2740cb9e962191c2e5799b01d4c23a4c5afa","observation_id":"e8fbd981-45eb-48d6-9617-ce72bf99ee65","resolution":{"observed_at":"2026-08-07T11:11:40.441575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.06538","last_updated":"2017-01-23T18:10:00Z","snapshot_observed_at":"2026-07-06T05:27:13.416519Z","submitted_at":"2017-01-23T18:10:00Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.06538","snapshot_observed_at":"2026-08-07T11:11:40.445540Z","title":"Outrageously large neural networks: The sparsely-gated mixture-of-experts layer.arXiv preprint arXiv:1701.06538, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.445540Z"},"links":{"cited_paper":"/paper/1701.06538","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:e9d11f3efa6afc3f930fe9d4789e2bd227c517bb6da4c2304ffa54bb338e9a17","observation_id":"85fc64ee-2038-44b9-b857-3bf9cc06b2e3","resolution":{"observed_at":"2026-08-07T11:11:40.445540Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.19650","last_updated":"2024-11-29T12:06:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-11-29T12:06:03Z","title":"CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.19650","snapshot_observed_at":"2026-08-07T11:11:40.448850Z","title":"Cogact: A foundational vision-language- action model for synergizing cognition and action in robotic manipulation, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.448850Z"},"links":{"cited_paper":"/paper/2411.19650","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:fdbfa759eb3de9cc696e794ad2d94f61c3d6eabb71fe1bfafe359ec8ab38d1aa","observation_id":"8aace697-34ed-43c3-914a-50c88905b990","resolution":{"observed_at":"2026-08-07T11:11:40.448850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.00861","last_updated":"2021-12-09T21:40:22Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-12-01T22:24:34Z","title":"A General Language Assistant as a Laboratory for Alignment","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.00861","snapshot_observed_at":"2026-08-07T11:11:40.452007Z","title":"A general language assistant as a laboratory for alignment.arXiv preprint arXiv:2112.00861, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.452007Z"},"links":{"cited_paper":"/paper/2112.00861","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:9c19aef262ed492bef1b5dd71402cbb3165be2bc1eef434e2894a2cc9aba83e1","observation_id":"1dd9723d-b75f-4f4b-8e87-6aa97ceca224","resolution":{"observed_at":"2026-08-07T11:11:40.452007Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:42.900514Z","title":"Regulating chatgpt and other large generative ai models","venue":null,"work_id":"66fcbf02-eefc-41ae-8b9a-acd63b363303","year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.455122Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:f1dea17e46667b4590833ec429d4ada39530026dab0aed2db069fff4535cb9d6","observation_id":"3b1a64ec-e3a2-4458-b5c2-5f6b6dabd9e5","resolution":{"observed_at":"2026-08-07T11:11:42.948942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:42.743450Z","title":"Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022","venue":null,"work_id":"410f5966-858e-4aab-a8d0-c1cbfe9f9bb3","year":2022},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.458043Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:ea9fd864833b6c4ab6ecc48cba73a70f2d9e69820b0b6ff168ca9facc7fe65a2","observation_id":"1f2ed3ec-f3c5-4faa-9f7c-bb8f1d2a5a3d","resolution":{"observed_at":"2026-08-07T11:11:42.782514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:42.593688Z","title":"Jailbroken: How does llm safety training fail?Advances in Neural Information Processing Systems, 36, 2024","venue":null,"work_id":"2bb716a9-0b84-404b-8aaa-b9b65a02c41f","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.461177Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:cb0b0c2faa014e9203cbcb40761022983ef633681448cf84a3c6caa3bcf6b8a1","observation_id":"a4bffa5c-d692-42cd-992c-46a087197421","resolution":{"observed_at":"2026-08-07T11:11:42.655018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:42.484494Z","title":"Are aligned neural networks adversarially aligned?Advances in Neural Information Processing Systems, 36, 2024","venue":null,"work_id":"cb38e569-7981-4111-9edf-dc93cfa59bf2","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.464457Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:bdf0b03ae0ba25ef1612645eb86f1b6ec2f0de0a5610e279e53ac9b1377f5849","observation_id":"fdc1b322-6605-44f4-92bc-3a0dbb4173f5","resolution":{"observed_at":"2026-08-07T11:11:42.548810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09024","last_updated":"2025-04-18T14:30:31Z","snapshot_observed_at":"2026-08-02T12:38:54.249632Z","submitted_at":"2024-10-11T17:39:22Z","title":"AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09024","snapshot_observed_at":"2026-08-07T11:11:40.467496Z","title":"Agentharm: A benchmark for measuring harmfulness of llm agents, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.467496Z"},"links":{"cited_paper":"/paper/2410.09024","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:a910972f6368d29994813e6ec713da0a29ce52f65e57f06136381e402d1f713e","observation_id":"878ebc4a-d52b-422e-8869-dff158b29204","resolution":{"observed_at":"2026-08-07T11:11:40.467496Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04984","last_updated":"2025-01-14T20:16:01Z","snapshot_observed_at":"2026-07-29T23:20:20.918596Z","submitted_at":"2024-12-06T12:09:50Z","title":"Frontier Models are Capable of In-context Scheming","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04984","snapshot_observed_at":"2026-08-07T11:11:40.470984Z","title":"Frontier models are capable of in-context scheming.arXiv preprint arXiv:2412.04984, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.470984Z"},"links":{"cited_paper":"/paper/2412.04984","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:22a3a1d37adce63b643d7bc26cd5ccba663eb85e1d11f094aad64ad5535bc313","observation_id":"7a5db577-51ce-41a8-a94c-fd43ca12a759","resolution":{"observed_at":"2026-08-07T11:11:40.470984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.19550","last_updated":"2024-05-29T22:26:26Z","snapshot_observed_at":"2026-07-06T18:22:18.644161Z","submitted_at":"2024-05-29T22:26:26Z","title":"Stress-Testing Capability Elicitation With Password-Locked Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.19550","snapshot_observed_at":"2026-08-07T11:11:40.474093Z","title":"Stress-testing capability elicitation with password-locked models.arXiv preprint arXiv:2405.19550, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.474093Z"},"links":{"cited_paper":"/paper/2405.19550","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:2e7f421688eaadda95c449e0843278669a2dacaf6587498e1047454705d23f97","observation_id":"81792aed-f23f-4c4b-b15f-3b7ae48bef03","resolution":{"observed_at":"2026-08-07T11:11:40.474093Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04893","last_updated":"2024-03-07T20:55:08Z","snapshot_observed_at":"2026-08-05T04:16:50.799588Z","submitted_at":"2024-03-07T20:55:08Z","title":"A Safe Harbor for AI Evaluation and Red Teaming","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04893","snapshot_observed_at":"2026-08-07T11:11:40.477043Z","title":"A safe harbor for ai evaluation and red teaming.arXiv preprint arXiv:2403.04893, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.477043Z"},"links":{"cited_paper":"/paper/2403.04893","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:e561afe284ecb89fe1d4a12e3576ec550a5704c17967a57b502045ff740fce8f","observation_id":"e41ed12b-0b24-4dd6-9bb1-47952bab1fa8","resolution":{"observed_at":"2026-08-07T11:11:40.477043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.14981","last_updated":"2025-04-16T09:38:09Z","snapshot_observed_at":"2026-07-06T18:49:33.987133Z","submitted_at":"2024-07-20T21:13:56Z","title":"Open Problems in Technical AI Governance","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.14981","snapshot_observed_at":"2026-08-07T11:11:40.480206Z","title":"Open problems in technical ai governance.arXiv preprint arXiv:2407.14981, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.480206Z"},"links":{"cited_paper":"/paper/2407.14981","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:de4e1afa3cf6953d063743bb8916b9852a70a77c1d90ab33eaf40399f251dcec","observation_id":"a50f1dbe-d4a2-4ed6-bbeb-2ce01e49fb71","resolution":{"observed_at":"2026-08-07T11:11:40.480206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04451","last_updated":"2024-03-20T21:34:56Z","snapshot_observed_at":"2026-08-06T02:57:30.438059Z","submitted_at":"2023-10-03T19:44:37Z","title":"AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04451","snapshot_observed_at":"2026-08-07T11:11:40.483280Z","title":"Autodan: Generating stealthy jailbreak prompts on aligned large language models.arXiv preprint arXiv:2310.04451, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.483280Z"},"links":{"cited_paper":"/paper/2310.04451","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:608c54669e084581ca827f75a4b962f8e2133167b838a688f8251199f1d45f17","observation_id":"3e69ab2f-f2d8-4b74-a925-d5125038e49d","resolution":{"observed_at":"2026-08-07T11:11:40.483280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:42.364488Z","title":"Visual adversarial examples jailbreak aligned large language models","venue":null,"work_id":"37445cda-fb39-44a7-a785-0fd42a16745b","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.486909Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:fb10600c03009f3676e022dbabf9449c9a95b032d98721a6ce1550e2378f4b35","observation_id":"b370fc59-43ab-4246-9e74-508814b52dfa","resolution":{"observed_at":"2026-08-07T11:11:42.405908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.15221","last_updated":"2024-09-04T00:58:59Z","snapshot_observed_at":"2026-07-06T19:06:41.697671Z","submitted_at":"2024-08-27T17:33:30Z","title":"LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.15221","snapshot_observed_at":"2026-08-07T11:11:40.490378Z","title":"Llm defenses are not robust to multi-turn human jailbreaks yet.arXiv preprint arXiv:2408.15221, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.490378Z"},"links":{"cited_paper":"/paper/2408.15221","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:7d663a880552fb190678d86dd3bd70cb7e7b6dece3d5712c9f1c8d14da15a033","observation_id":"ea5b7d3f-4fcd-41a9-bb98-f17d2047398d","resolution":{"observed_at":"2026-08-07T11:11:40.490378Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.01833","last_updated":"2025-02-26T13:41:41Z","snapshot_observed_at":"2026-08-03T07:26:39.431128Z","submitted_at":"2024-04-02T10:45:49Z","title":"Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.01833","snapshot_observed_at":"2026-08-07T11:11:40.493528Z","title":"Great, now write an article about that: The crescendo multi-turn llm jailbreak attack.arXiv preprint arXiv:2404.01833, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.493528Z"},"links":{"cited_paper":"/paper/2404.01833","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:6d1b180bcaa9063245f879a93dd200fac7d74d0ab64c494783d0c4472d38e168","observation_id":"aed2d884-f9d4-4301-9d15-bace8a2c0e14","resolution":{"observed_at":"2026-08-07T11:11:40.493528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:42.227300Z","title":"Improving alignment and robustness with circuit breakers","venue":null,"work_id":"2c027fea-fa40-4db2-9b34-93bd1dc0b29e","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.497097Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:8680a9c05f952a52c59675eb1b6b520a4d84c2ebf0078187f7dd69a8028bf417","observation_id":"7ecf9ed4-023e-45d3-aeec-6358a25a357e","resolution":{"observed_at":"2026-08-07T11:11:42.312697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03684","last_updated":"2024-06-11T19:02:52Z","snapshot_observed_at":"2026-07-06T16:28:22.350574Z","submitted_at":"2023-10-05T17:01:53Z","title":"SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03684","snapshot_observed_at":"2026-08-07T11:11:40.500019Z","title":"Smoothllm: Defending large language models against jailbreaking attacks.arXiv preprint arXiv:2310.03684, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.500019Z"},"links":{"cited_paper":"/paper/2310.03684","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:6cfc6890dea4a74d5bdb80b2784510b45f23e992ce29ef7789f2c54232e81c0f","observation_id":"f9bc86cb-b49f-4797-a4a8-b8e8efc55350","resolution":{"observed_at":"2026-08-07T11:11:40.500019Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-08-07T11:11:40.503166Z","title":"Openai o1 system card.arXiv preprint arXiv:2412.16720, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.503166Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:3b2a7dd8bf1de301901332de71b7af6a3ba9759ded6a952de91a59f7f63881b4","observation_id":"c8c0b561-2586-42fe-ba9a-8ef06af55522","resolution":{"observed_at":"2026-08-07T11:11:40.503166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-07T11:11:40.506433Z","title":"The llama 3 herd of models.arXiv preprint arXiv:2407.21783, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.506433Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:59e2bd879851ae1850b8bc2cb591e3e254787b94ccccb9c3d287d1e64080358c","observation_id":"dfc03a1d-a0fc-48df-9b31-4379c8b5300e","resolution":{"observed_at":"2026-08-07T11:11:40.506433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.12814","last_updated":"2025-02-04T20:02:17Z","snapshot_observed_at":"2026-08-08T10:00:10.515051Z","submitted_at":"2024-06-18T17:32:48Z","title":"Dissecting Adversarial Robustness of Multimodal LM Agents","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.12814","snapshot_observed_at":"2026-08-07T11:11:40.509846Z","title":"Adversarial attacks on multimodal agents.arXiv preprint arXiv:2406.12814, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.509846Z"},"links":{"cited_paper":"/paper/2406.12814","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:ec16a57b249df444c1a746bb11e628e45aeb3586a6eea51a99624a72996feb46","observation_id":"98b16650-4cd2-4544-817b-1fc5a857bd5b","resolution":{"observed_at":"2026-08-07T11:11:40.509846Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.03007","last_updated":"2024-06-05T07:14:28Z","snapshot_observed_at":"2026-07-06T18:25:44.620682Z","submitted_at":"2024-06-05T07:14:28Z","title":"BadAgent: Inserting and Activating Backdoor Attacks in LLM Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.03007","snapshot_observed_at":"2026-08-07T11:11:40.513409Z","title":"Badagent: Inserting and activating backdoor attacks in llm agents.arXiv preprint arXiv:2406.03007, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.513409Z"},"links":{"cited_paper":"/paper/2406.03007","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:58c39f9bf8cac8739d0134a2395ac725124d57ac5e92b0ef27caa6631198270e","observation_id":"f3f856b1-b0bf-43af-a1cc-44626b5a8be5","resolution":{"observed_at":"2026-08-07T11:11:40.513409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.18382","last_updated":"2024-07-02T08:56:48Z","snapshot_observed_at":"2026-07-06T18:37:21.973331Z","submitted_at":"2024-06-26T14:24:51Z","title":"Adversarial Search Engine Optimization for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.18382","snapshot_observed_at":"2026-08-07T11:11:40.516945Z","title":"Adversarial search engine optimiza- tion for large language models.arXiv preprint arXiv:2406.18382, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.516945Z"},"links":{"cited_paper":"/paper/2406.18382","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:77b3bce7b59d1143ecf0ec7df1d797dd83b6c3759f28479fb4125624135536b3","observation_id":"5365cf22-08b9-4730-9778-c3bf52a2e170","resolution":{"observed_at":"2026-08-07T11:11:40.516945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.18676","last_updated":"2025-02-10T16:32:27Z","snapshot_observed_at":"2026-07-06T19:58:13.816588Z","submitted_at":"2024-11-27T18:57:26Z","title":"Embodied Red Teaming for Auditing Robotic Foundation Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.18676","snapshot_observed_at":"2026-08-07T11:11:40.520328Z","title":"Embodied red teaming for auditing robotic foundation models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.520328Z"},"links":{"cited_paper":"/paper/2411.18676","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:d259755c979f7ef86b3863a591c2d33aad0122eb979657315754b0f091140d2b","observation_id":"a04af57b-0804-441e-9000-44ea52aa744a","resolution":{"observed_at":"2026-08-07T11:11:40.520328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6199","last_updated":"2014-02-19T16:33:14Z","snapshot_observed_at":"2026-07-06T03:31:33.797310Z","submitted_at":"2013-12-21T03:36:08Z","title":"Intriguing properties of neural networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6199","snapshot_observed_at":"2026-08-07T11:11:40.523904Z","title":"Intriguing properties of neural networks.arXiv preprint arXiv:1312.6199, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.523904Z"},"links":{"cited_paper":"/paper/1312.6199","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:efee2496e033cf28e7a05b2d6e8c1c41e86bf6fbb2a809ad4b8e9daa5ff955a3","observation_id":"1fba4143-4ab4-4792-8c3a-9c11a96de4a1","resolution":{"observed_at":"2026-08-07T11:11:40.523904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.06083","last_updated":"2019-09-04T18:53:10Z","snapshot_observed_at":"2026-08-07T14:27:46.872660Z","submitted_at":"2017-06-19T17:53:11Z","title":"Towards Deep Learning Models Resistant to Adversarial Attacks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.06083","snapshot_observed_at":"2026-08-07T11:11:40.527358Z","title":"Towards deep learning models resistant to adversarial attacks.arXiv preprint arXiv:1706.06083, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.527358Z"},"links":{"cited_paper":"/paper/1706.06083","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:02ba136f71dba2687d0ebdc86190380e58cc3861e94a0d001a5933f9f5fffad1","observation_id":"2d667f05-5244-47b9-886d-539fdc725335","resolution":{"observed_at":"2026-08-07T11:11:40.527358Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.03348","last_updated":"2023-11-24T12:50:31Z","snapshot_observed_at":"2026-08-05T10:39:14.391116Z","submitted_at":"2023-11-06T18:55:18Z","title":"Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.03348","snapshot_observed_at":"2026-08-07T11:11:40.530536Z","title":"Scalable and transferable black-box jailbreaks for language models via persona modulation.arXiv preprint arXiv:2311.03348, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.530536Z"},"links":{"cited_paper":"/paper/2311.03348","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:79e1f25488e4bec3c525ed427c330a2d6730bfa8ac69a2206c8c45920efb115a","observation_id":"3c0bbdf6-817c-4bd0-a666-601b851f6a74","resolution":{"observed_at":"2026-08-07T11:11:40.530536Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.17237","last_updated":"2023-11-03T19:15:51Z","snapshot_observed_at":"2026-07-06T15:48:32.547396Z","submitted_at":"2023-06-29T18:06:15Z","title":"HYDRA: Hybrid Robot Actions for Imitation Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.17237","snapshot_observed_at":"2026-08-07T11:11:40.534332Z","title":"Hydra: Hybrid robot actions for imitation learning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.534332Z"},"links":{"cited_paper":"/paper/2306.17237","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:d105c8d97062efb9de703c1cc946802b09c712cb9d2e50e972e0cfd23803b03d","observation_id":"a40bcbbd-e932-475c-a08d-3e8861d51d2d","resolution":{"observed_at":"2026-08-07T11:11:40.534332Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.05941","last_updated":"2024-05-09T17:30:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-05-09T17:30:16Z","title":"Evaluating Real-World Robot Manipulation Policies in Simulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.05941","snapshot_observed_at":"2026-08-07T11:11:40.538116Z","title":"Evaluating real-world robot manipulation policies in simulation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.538116Z"},"links":{"cited_paper":"/paper/2405.05941","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:60a9022d38bd14f229f7d652cc0716859b108c08c13467cd596bf0613d8d1633","observation_id":"bc765adb-df3b-4956-a7c0-7499f5f3f0f0","resolution":{"observed_at":"2026-08-07T11:11:40.538116Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.10345","last_updated":"2025-06-05T21:26:08Z","snapshot_observed_at":"2026-08-02T17:44:41.340688Z","submitted_at":"2024-12-13T18:40:51Z","title":"TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.10345","snapshot_observed_at":"2026-08-07T11:11:40.541709Z","title":"Tracevla: Visual trace prompting enhances spatial-temporal awareness for generalist robotic policies, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.541709Z"},"links":{"cited_paper":"/paper/2412.10345","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:b70d196ef71308151ab0139e4dc3cd2750f2d097e28a372ca443dc8d318f61ea","observation_id":"149d46b6-f86a-47fa-82d7-2d7afc0d3ee0","resolution":{"observed_at":"2026-08-07T11:11:40.541709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:42.030787Z","title":"GitHub - allenzren/open-pi-zero: Re-implementation of pi0 vision-language-action (VLA) model from Physical Intelligence — github.com","venue":null,"work_id":"1f86da15-75b0-4bce-860c-c94961fce619","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.544923Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:07275e67c13e02000f71b936017e8d387a41bc41efd62488f519d8e1886966b1","observation_id":"fd157157-cf82-437d-b9f5-72fad7cbaeb3","resolution":{"observed_at":"2026-08-07T11:11:42.134928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:41.903577Z","title":"Failures to find transferable image jailbreaks between vision-language models","venue":null,"work_id":"2625b250-30e7-41eb-8c6e-920c65310267","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.547821Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:e3783fcbc0a69bd1065209ff00c36c523085745081510c4b7f43b3f9c1d72c4a","observation_id":"0634483d-8172-449a-bfcc-5c817b073cd5","resolution":{"observed_at":"2026-08-07T11:11:41.952328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06387","last_updated":"2024-05-25T07:01:15Z","snapshot_observed_at":"2026-08-06T13:25:52.403871Z","submitted_at":"2023-10-10T07:50:29Z","title":"Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06387","snapshot_observed_at":"2026-08-07T11:11:40.551096Z","title":"Jailbreak and guard aligned language models with only few in-context demonstrations.arXiv preprint arXiv:2310.06387,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.551096Z"},"links":{"cited_paper":"/paper/2310.06387","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:1e0cf599b85ec727c46d126521509914414c62730541aec6c4afb5bb504ec85b","observation_id":"60f67dd0-5532-4871-9215-078dcc65b23a","resolution":{"observed_at":"2026-08-07T11:11:40.551096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.00614","last_updated":"2023-09-04T17:47:36Z","snapshot_observed_at":"2026-07-06T16:13:23.343694Z","submitted_at":"2023-09-01T17:59:44Z","title":"Baseline Defenses for Adversarial Attacks Against Aligned Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.00614","snapshot_observed_at":"2026-08-07T11:11:40.554404Z","title":"Baseline de- fenses for adversarial attacks against aligned language models.arXiv preprint arXiv:2309.00614,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.554404Z"},"links":{"cited_paper":"/paper/2309.00614","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:e76c1313408354e35b99e4a363176d114189c18201ca5ba89d73cca96beadfb9","observation_id":"d1f6c3b4-8554-4a04-9e30-2071d3ed7753","resolution":{"observed_at":"2026-08-07T11:11:40.554404Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05862","last_updated":"2022-04-12T15:02:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-12T15:02:38Z","title":"Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05862","snapshot_observed_at":"2026-08-07T11:11:40.557735Z","title":"Training a helpful and harmless assistant with reinforcement learning from human feedback, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.557735Z"},"links":{"cited_paper":"/paper/2204.05862","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:08e65a69249d3b01383c0d98fc71bbebef1e5ada0071de1d9bb02abcbed12426","observation_id":"e2885798-5bb7-4b89-90b1-3f90f216a57e","resolution":{"observed_at":"2026-08-07T11:11:40.557735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03741","last_updated":"2023-02-17T17:00:34Z","snapshot_observed_at":"2026-08-03T14:31:51.401500Z","submitted_at":"2017-06-12T17:23:59Z","title":"Deep reinforcement learning from human preferences","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03741","snapshot_observed_at":"2026-08-07T11:11:40.561507Z","title":"Brown, Miljan Martic, Shane Legg, and Dario Amodei","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.561507Z"},"links":{"cited_paper":"/paper/1706.03741","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:bc2b03b7730e0a87f7fe06f1378f3c57dc7f61258cddde4abae9d0bbd3728b41","observation_id":"90d52dea-0a17-49c8-9875-b97aa91dd09c","resolution":{"observed_at":"2026-08-07T11:11:40.561507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.07871","last_updated":"2018-11-19T18:48:04Z","snapshot_observed_at":"2026-07-06T07:15:51.575438Z","submitted_at":"2018-11-19T18:48:04Z","title":"Scalable agent alignment via reward modeling: a research direction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.07871","snapshot_observed_at":"2026-08-07T11:11:40.565294Z","title":"Scalable agent alignment via reward modeling: a research direction, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.565294Z"},"links":{"cited_paper":"/paper/1811.07871","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:9375af45c4c080578babca05b2239b9afd51d7ba0070ad07a20554b174c2e200","observation_id":"45a0b585-35d0-4e79-b213-a2c76e17bc74","resolution":{"observed_at":"2026-08-07T11:11:40.565294Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04249","last_updated":"2024-02-27T04:43:08Z","snapshot_observed_at":"2026-07-06T17:26:23.067923Z","submitted_at":"2024-02-06T18:59:08Z","title":"HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04249","snapshot_observed_at":"2026-08-07T11:11:40.568661Z","title":"Harmbench: A standardized evaluation framework for automated red teaming and robust refusal, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.568661Z"},"links":{"cited_paper":"/paper/2402.04249","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:6f0805b11f4e97795cbd0efd506332335647d0289301281910d3022994c8a334","observation_id":"b5a7b127-a24d-4762-b079-14c90623e9ff","resolution":{"observed_at":"2026-08-07T11:11:40.568661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.19309","last_updated":"2025-02-04T08:49:11Z","snapshot_observed_at":"2026-07-31T23:24:14.896271Z","submitted_at":"2024-11-28T18:30:10Z","title":"GRAPE: Generalizing Robot Policy via Preference Alignment","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.19309","snapshot_observed_at":"2026-08-07T11:11:40.572064Z","title":"Grape: Generalizing robot policy via preference alignment.arXiv preprint arXiv:2411.19309, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.572064Z"},"links":{"cited_paper":"/paper/2411.19309","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:7f3374a9eb919154ae707437374906c7307ddac101a1918355d7adb90be4b124","observation_id":"4bface85-924a-42ee-a04b-36476e85f515","resolution":{"observed_at":"2026-08-07T11:11:40.572064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:41.720648Z","title":"Abbas, Shakra Mehak, Georgios C","venue":null,"work_id":"21168e75-0ea1-4023-82e5-61bdb9785921","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.575417Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:2e2e2e0ef7dcc83b20e2165fac4c3705e32effb5880709ca13966f2da76d08e5","observation_id":"44e5a0f2-5daa-40d8-9f27-de07fa26d6d0","resolution":{"observed_at":"2026-08-07T11:11:41.806984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.03480","last_updated":"2026-04-19T06:23:17Z","snapshot_observed_at":"2026-07-30T14:07:10.544745Z","submitted_at":"2025-03-05T13:16:55Z","title":"SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.03480","snapshot_observed_at":"2026-08-07T11:11:40.578496Z","title":"Safevla: Towards safety alignment of vision-language-action model via safe reinforcement learning.arXiv preprint arXiv:2503.03480, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.578496Z"},"links":{"cited_paper":"/paper/2503.03480","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:5287640feda5ef5ea577f3c78fe00bd3ab3758c5cdfafef19162529139de9311","observation_id":"c8df0c7d-307e-485e-ae5e-048422841b12","resolution":{"observed_at":"2026-08-07T11:11:40.578496Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.582432Z","title":"Safety guardrails for llm-enabled robots.arXiv preprint arXiv:2503.07885, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.582432Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:d8335da009c7a30029fce0c1f077b72efe6e2ff5d8b68fc8e11e51ef74096d3c","observation_id":"67b24b70-5179-4f26-b95c-7f1ef6f9c7f9","resolution":{"observed_at":"2026-08-07T11:11:40.582432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:41.583195Z","title":"pick coke can","venue":null,"work_id":"ec38fdd2-c15a-4bfc-8d81-3eb4a6d95e97","year":2024},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.585654Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:37320e1b4c6b76a29416b8483eb022e924e349c3e598a02186e3896b94b4ccc6","observation_id":"bd3044df-29b1-4895-ab51-4291ae069659","resolution":{"observed_at":"2026-08-07T11:11:41.661182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:11:40.291167Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.291167Z"},"links":{"citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:53bfd00e2815a9f24e51dafe5c5640ca53a768d8bfe72eb6aca4d1231143d4e2","observation_id":"8a317e3e-f960-47ea-89e2-8c58204d714b","resolution":{"observed_at":"2026-08-07T11:11:40.291167Z","resolver_source":null,"status":"parse_uncertain"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12871","last_updated":"2024-05-09T17:35:44Z","snapshot_observed_at":"2026-08-05T10:01:43.401012Z","submitted_at":"2023-11-18T01:21:38Z","title":"An Embodied Generalist Agent in 3D World","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12871","snapshot_observed_at":"2026-08-07T11:11:40.428658Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T11:11:40.428658Z"},"links":{"cited_paper":"/paper/2311.12871","citing_paper":"/paper/2506.03350"},"observation_digest":"sha256:3e356c5b1019e3defbc1f821891a9befe52525e80b3f29618c34a09ae97e400e","observation_id":"0ac6cac2-4c25-4831-94ea-903e4988266f","resolution":{"observed_at":"2026-08-07T11:11:40.428658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.03350","last_updated":"2025-06-03T19:43:58Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-09T00:38:29.639641Z","submitted_at":"2025-06-03T19:43:58Z","title":"Adversarial Attacks on Robotic Vision Language Action Models"},"reference_resolution":{"displayed":95,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":1,"unresolved":80,"verified_exact":1,"verified_fuzzy":11},"total_outbound_references":95},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 95 of 95 outbound references and 18 inbound Pith citation observations for arXiv:2506.03350."}