{"as_of":"2026-08-18T07:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1cf8b5b47bf97fe8513c65e277d67b81f540d5721f682c61a43d4c0ff68a91ae","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":37,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":37,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":37,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:10:31.093405Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-09T10:26:11.076263Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2407.04295","last_updated":"2024-08-30T11:57:47Z","snapshot_observed_at":"2026-08-12T17:45:10.384900Z","submitted_at":"2024-07-05T06:57:30Z","title":"Jailbreak Attacks and Defenses Against Large Language Models: A Survey","version":2},"reference_index":110,"source":"pdf_text","source_observed_at":"2026-05-15T02:20:44.368219Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2407.04295"},"observation_digest":"sha256:7239d304a7d4a8f7165ab8e1c1b0c8797517ebf52d05cedc05a3a2e976cd134a","observation_id":"2dcc7f64-d806-45fe-8dd4-bcce51bdd1fc","resolution":{"observed_at":"2026-05-15T02:20:44.468173Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-12T12:56:34.447996Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16642","last_updated":"2024-11-25T18:23:58Z","snapshot_observed_at":"2026-08-16T04:31:15.591318Z","submitted_at":"2024-11-25T18:23:58Z","title":"Preventing Jailbreak Prompts as Malicious Tools for Cybercriminals: A Cyber Defense Perspective","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-12T12:56:34.447996Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2411.16642"},"observation_digest":"sha256:de1fed22fc7c422f914f6a2c546260614dfbca820e0e3c49015bae9bcb7c83a6","observation_id":"a0d05ba6-b761-453e-b545-d5a28031f29f","resolution":{"observed_at":"2026-08-12T12:56:34.447996Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-12T12:50:17.181702Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.16905","last_updated":"2024-11-25T20:16:16Z","snapshot_observed_at":"2026-08-14T17:17:32.244720Z","submitted_at":"2024-11-25T20:16:16Z","title":"Boundless Socratic Learning with Language Games","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T12:50:17.181702Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2411.16905"},"observation_digest":"sha256:a6f2c33cd3703638a0d8d4093f5e9c32010cb43b295a117707c15276b6b189fd","observation_id":"d13057ea-efe0-42db-9eed-43781c6f70b3","resolution":{"observed_at":"2026-08-12T12:50:17.181702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-11T18:53:15.514755Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10423","last_updated":"2025-04-14T12:52:24Z","snapshot_observed_at":"2026-08-13T05:21:45.958780Z","submitted_at":"2024-12-10T12:42:33Z","title":"Look Before You Leap: Enhancing Attention and Vigilance Regarding Harmful Content with GuidelineLLM","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-11T18:53:15.514755Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2412.10423"},"observation_digest":"sha256:d32fcfd0d159f1dd7d67f2900f109b0adcbe83213ae4b86020a2abb835565592","observation_id":"098a5ccf-bdb8-4385-a41f-96c0fc9ef065","resolution":{"observed_at":"2026-08-11T18:53:15.514755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-10T19:08:01.769602Z","title":", author Wu, Y","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.10639","last_updated":"2025-05-30T03:31:24Z","snapshot_observed_at":"2026-08-16T08:22:51.927618Z","submitted_at":"2025-01-18T02:57:12Z","title":"Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks","version":3},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-10T19:08:01.769602Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2501.10639"},"observation_digest":"sha256:81644533a615f7dcbe51e7af466955a8f3a2cd8b6ef15706f5bc3497b7a6130c","observation_id":"f76712e0-a05a-4230-92d8-9c76d534f4a9","resolution":{"observed_at":"2026-08-10T19:08:01.769602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2503.21460","last_updated":"2025-03-27T12:50:17Z","snapshot_observed_at":"2026-07-06T20:59:35.694800Z","submitted_at":"2025-03-27T12:50:17Z","title":"Large Language Model Agent: A Survey on Methodology, Applications and Challenges","version":1},"reference_index":188,"source":"pdf_text","source_observed_at":"2026-05-22T21:51:34.309870Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2503.21460"},"observation_digest":"sha256:462d9208ac1d0b6a7b25494562bef6bc148ae8220f3039320adc939fea24e820","observation_id":"77d6c430-4514-4969-9bfa-f424bdae5aa0","resolution":{"observed_at":"2026-05-22T21:52:10.697219Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-16T12:10:31.093405Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.13562","last_updated":"2025-04-18T09:02:12Z","snapshot_observed_at":"2026-08-17T15:26:10.256287Z","submitted_at":"2025-04-18T09:02:12Z","title":"DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-16T12:10:31.093405Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2504.13562"},"observation_digest":"sha256:067bf6e614aa43c72b6312ebc8cc60676b6ff7ded46224e94e2c7d4f87e3fb4d","observation_id":"e0e1ef83-954b-4e3d-baf3-6fe8801ae300","resolution":{"observed_at":"2026-08-16T12:10:31.093405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-16T11:31:11.238811Z","title":"Autodefense: Multi- agent llm defense against jailbreak attacks.arXiv preprint arXiv:2403.04783, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.15512","last_updated":"2025-04-26T16:17:55Z","snapshot_observed_at":"2026-08-18T00:47:28.167584Z","submitted_at":"2025-04-22T01:18:42Z","title":"T2VShield: Model-Agnostic Jailbreak Defense for Text-to-Video Models","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-16T11:31:11.238811Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2504.15512"},"observation_digest":"sha256:6c7ec1b566d27ea439b09242f374a16b0946d9623342cb26b0f3271acdd7044b","observation_id":"c9f61786-26dd-48ea-83e1-d3002b0515cc","resolution":{"observed_at":"2026-08-16T11:31:11.238811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-16T04:33:06.622439Z","title":"Autod efense: Multi-agent llm defense against jailbreak attacks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.00976","last_updated":"2025-05-02T03:37:52Z","snapshot_observed_at":"2026-08-16T04:28:01.145316Z","submitted_at":"2025-05-02T03:37:52Z","title":"Attack and defense techniques in large language models: A survey and new perspectives","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-16T04:33:06.622439Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2505.00976"},"observation_digest":"sha256:9c0ec810984c1f68ba0b74d93e508052918b9ae94332571a35cdd397864f1928","observation_id":"c252686f-dd82-4de3-9377-8ba484070689","resolution":{"observed_at":"2026-08-16T04:33:06.622439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-16T04:28:00.922999Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.01177","last_updated":"2025-05-02T10:35:26Z","snapshot_observed_at":"2026-08-16T14:20:05.929905Z","submitted_at":"2025-05-02T10:35:26Z","title":"LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures","version":1},"reference_index":165,"source":"pdf_text","source_observed_at":"2026-08-16T04:28:00.922999Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2505.01177"},"observation_digest":"sha256:d7f898912110e2680965e5c921776a4cfd9be9bf5af7e617a1eef72323d38e45","observation_id":"f3dfc389-8db7-4198-a553-00d97d2002e2","resolution":{"observed_at":"2026-08-16T04:28:00.922999Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-07T15:08:13.830889Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16241","last_updated":"2025-05-26T02:28:07Z","snapshot_observed_at":"2026-08-14T06:52:38.334219Z","submitted_at":"2025-05-22T05:19:42Z","title":"Three Minds, One Legend: Jailbreak Large Reasoning Model with Adaptive Stacked Ciphers","version":3},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T15:08:13.830889Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2505.16241"},"observation_digest":"sha256:59506cc245eec9546cdfb987d1485e69e1239e4f2071a532dd213becc8277f91","observation_id":"e12043b5-dbbc-450a-a216-c17e72b6f728","resolution":{"observed_at":"2026-08-07T15:08:13.830889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-07T13:02:45.177061Z","title":"Autodefense: Multi- agent llm defense against jailbreak attacks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22960","last_updated":"2025-06-20T03:07:38Z","snapshot_observed_at":"2026-08-13T19:16:19.923064Z","submitted_at":"2025-05-29T01:02:55Z","title":"Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T13:02:45.177061Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2505.22960"},"observation_digest":"sha256:a03c60095bf6c0fc3256044b2b2fc0bb31c9cfd0a751a7f031a2e534e83a1261","observation_id":"35c4c82a-a13b-483a-8835-afb609c51de4","resolution":{"observed_at":"2026-08-07T13:02:45.177061Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-07T12:11:26.034395Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05376","last_updated":"2025-06-09T05:48:22Z","snapshot_observed_at":"2026-08-16T08:19:36.098867Z","submitted_at":"2025-05-30T22:58:54Z","title":"A Red Teaming Roadmap Towards System-Level Safety","version":2},"reference_index":105,"source":"pdf_text","source_observed_at":"2026-08-07T12:11:26.034395Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2506.05376"},"observation_digest":"sha256:0e310bd01f0b6173257dc908f920fb4b464f9fbddb2bf5483a6b2466572eeb71","observation_id":"25943294-4e36-4a9f-9906-151cb48001dd","resolution":{"observed_at":"2026-08-07T12:11:26.034395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-07T10:17:26.862405Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.11094","last_updated":"2025-10-30T06:22:33Z","snapshot_observed_at":"2026-08-13T12:53:10.459412Z","submitted_at":"2025-06-06T05:50:50Z","title":"The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-07T10:17:26.862405Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2506.11094"},"observation_digest":"sha256:fd470e5c31fbae269e717073bbfc78822ffada5cb01d9e6f7dc6be97fcd2d7c8","observation_id":"20c6fe58-3282-48ed-ad79-6b3d4083e531","resolution":{"observed_at":"2026-08-07T10:17:26.862405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-07T00:46:10.506745Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12699","last_updated":"2025-06-19T06:30:24Z","snapshot_observed_at":"2026-08-14T17:40:51.768214Z","submitted_at":"2025-06-15T03:14:03Z","title":"SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation","version":2},"reference_index":138,"source":"pdf_text","source_observed_at":"2026-08-07T00:46:10.506745Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2506.12699"},"observation_digest":"sha256:0a1e71de7eb8c9c86ddcedfa1f4aac8bce347dbba76dde459092cf41e9f991a3","observation_id":"55fb3ae3-8746-46bf-a422-91928754ac8c","resolution":{"observed_at":"2026-08-07T00:46:10.506745Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-07T00:51:16.836659Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12707","last_updated":"2025-06-15T03:39:13Z","snapshot_observed_at":"2026-08-17T18:05:58.820120Z","submitted_at":"2025-06-15T03:39:13Z","title":"SecurityLingua: Efficient Defense of LLM Jailbreak Attacks via Security-Aware Prompt Compression","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-07T00:51:16.836659Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2506.12707"},"observation_digest":"sha256:0ec7b2943bce13850be7dd777a604c39de94e4c01b4e8bf3ec9e9d124270ba38","observation_id":"96fd0665-3084-4a7e-82af-daa38dcc1b51","resolution":{"observed_at":"2026-08-07T00:51:16.836659Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2506.17299","last_updated":"2026-04-24T04:36:54Z","snapshot_observed_at":"2026-08-02T14:45:34.223522Z","submitted_at":"2025-06-17T20:37:29Z","title":"Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-19T08:40:56.186349Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2506.17299"},"observation_digest":"sha256:fa34cbdf221c8342fd68e8600f90f437ef91aa637c204d3b3bc68da7b55f2417","observation_id":"661181d5-bd27-468d-bc24-180d16b4f5f6","resolution":{"observed_at":"2026-05-19T08:42:12.890039Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-06T22:55:09.189483Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20415","last_updated":"2025-06-25T13:31:13Z","snapshot_observed_at":"2026-08-17T07:20:36.298671Z","submitted_at":"2025-06-25T13:31:13Z","title":"SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T22:55:09.189483Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2506.20415"},"observation_digest":"sha256:bc1f2bd862353793ca2fdc2d3e168daf31fbe3f16b47c178aab09139b3a9c10d","observation_id":"e17440da-2c71-4720-b4c8-554849d03e38","resolution":{"observed_at":"2026-08-06T22:55:09.189483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-06T21:41:33.012697Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.23576","last_updated":"2025-06-30T07:29:07Z","snapshot_observed_at":"2026-08-17T01:05:41.623124Z","submitted_at":"2025-06-30T07:29:07Z","title":"Evaluating Multi-Agent Defences Against Jailbreaking Attacks on Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T21:41:33.012697Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2506.23576"},"observation_digest":"sha256:54957a752a9f2ea04ddc1c5a93852c5489e28de6aeeee9e6ca0638fed9905994","observation_id":"f41a7bbc-2b48-4cb1-b593-8e1176907018","resolution":{"observed_at":"2026-08-06T21:41:33.012697Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-06T18:56:56.942963Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06908","last_updated":"2025-07-09T14:46:32Z","snapshot_observed_at":"2026-08-15T10:57:36.359000Z","submitted_at":"2025-07-09T14:46:32Z","title":"MIND: A Multi-agent Framework for Zero-shot Harmful Meme Detection","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-06T18:56:56.942963Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2507.06908"},"observation_digest":"sha256:8b7b162b881bc77d0bda11fb70619a7a285f59a41bcb8738548ce026d4fd0e63","observation_id":"7041c1e2-d6ea-4233-86d3-70ca0cd1eaec","resolution":{"observed_at":"2026-08-06T18:56:56.942963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-06T18:28:25.260410Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08892","last_updated":"2025-07-10T22:31:09Z","snapshot_observed_at":"2026-08-18T06:08:25.354274Z","submitted_at":"2025-07-10T22:31:09Z","title":"Multi-Actor Generative Artificial Intelligence as a Game Engine","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T18:28:25.260410Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2507.08892"},"observation_digest":"sha256:14c4449cfb21161ea048afde0e5b07a919aeed74c9a8a9a13ccd2a59000b35ad","observation_id":"1c5a84dd-3a68-45a3-b162-74353007e0d2","resolution":{"observed_at":"2026-08-06T18:28:25.260410Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2507.14201","last_updated":"2026-05-01T04:31:46Z","snapshot_observed_at":"2026-08-11T04:21:18.267564Z","submitted_at":"2025-07-14T17:06:26Z","title":"ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-19T04:37:33.942379Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2507.14201"},"observation_digest":"sha256:802636f1eee7ee5b190a240b4d6eacfc1d743c82756300290c19d70929ab9060","observation_id":"331f0a6e-6396-4d20-a2e5-9d131f820e8d","resolution":{"observed_at":"2026-05-19T04:42:04.699000Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-05T22:24:23.450421Z","title":"Autodefense: Multi- agent llm defense against jailbreak attacks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.07139","last_updated":"2025-08-10T01:59:07Z","snapshot_observed_at":"2026-08-10T21:58:51.152330Z","submitted_at":"2025-08-10T01:59:07Z","title":"A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T22:24:23.450421Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2508.07139"},"observation_digest":"sha256:8484c45a2d4416ad6154320df3ac3162f87a7b3591f0c01ca678677c7dfe7498","observation_id":"f41039d3-9d9d-411b-99f0-e8eda572e6bf","resolution":{"observed_at":"2026-08-05T22:24:23.450421Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-05T10:44:10.627459Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03787","last_updated":"2025-09-04T00:45:58Z","snapshot_observed_at":"2026-08-18T00:30:11.532287Z","submitted_at":"2025-09-04T00:45:58Z","title":"Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-05T10:44:10.627459Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2509.03787"},"observation_digest":"sha256:e6cc5213f9406a55ddbb786bc4de04c46a930fbbb653f37c25039df1a820de9b","observation_id":"6a78fe27-3580-4bdf-95e6-6f4d72bcf790","resolution":{"observed_at":"2026-08-05T10:44:10.627459Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-04T09:25:58.229752Z","title":"Autodefense: Multi-agent LLM defense against jailbreak attacks.CoRR, abs/2403.04783, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.15476","last_updated":"2026-07-04T04:20:15Z","snapshot_observed_at":"2026-08-14T22:20:04.981358Z","submitted_at":"2025-10-17T09:38:54Z","title":"SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses","version":3},"reference_index":228,"source":"pdf_text","source_observed_at":"2026-08-04T09:25:58.229752Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2510.15476"},"observation_digest":"sha256:5cfda0779f90008014c1a5bc1bffb90b1cd038eddb2392bad038e8ac62e43a17","observation_id":"c31e2c17-d4e9-45b0-98b1-b8c18bbedec8","resolution":{"observed_at":"2026-08-04T09:25:58.229752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2510.22628","last_updated":"2026-05-01T17:57:58Z","snapshot_observed_at":"2026-08-13T19:44:16.113742Z","submitted_at":"2025-10-26T11:19:47Z","title":"Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-18T04:22:54.943043Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2510.22628"},"observation_digest":"sha256:98a901c5bdd7858cbed3c8f5b17d9688d5f5aedf8bffe6815bc767578b7867ed","observation_id":"e636f8af-8f02-4e4f-b995-b87b5480e453","resolution":{"observed_at":"2026-05-18T04:25:52.204540Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2511.00181","last_updated":"2026-04-07T09:06:09Z","snapshot_observed_at":"2026-08-14T22:01:59.522171Z","submitted_at":"2025-10-31T18:36:49Z","title":"From Evidence to Verdict: An Agent-Based Forensic Framework for AI-Generated Image Detection","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-18T02:04:49.742067Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2511.00181"},"observation_digest":"sha256:4514366ba699dc5a2e4c700e3f62cbd9658b51fef75682149424a9ae549a3a3d","observation_id":"ff1a4df8-4f67-4ee6-a596-00bcdeae6c8b","resolution":{"observed_at":"2026-05-18T02:05:38.955901Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-02T23:52:40.608795Z","title":"naacl-long.92/","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.12418","last_updated":"2026-06-27T01:07:47Z","snapshot_observed_at":"2026-08-09T09:16:47.762774Z","submitted_at":"2026-02-12T21:17:32Z","title":"Sparse Autoencoders are Capable LLM Jailbreak Mitigators","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-02T23:52:40.608795Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2602.12418"},"observation_digest":"sha256:f3b5b586e701e16565227fcf6b8b383e1b2e43f311dbb1cca5b1e1e5cab11390","observation_id":"191d38ee-d039-4b79-aec7-4800c10e19da","resolution":{"observed_at":"2026-08-02T23:52:40.608795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2604.24477","last_updated":"2026-04-27T13:45:14Z","snapshot_observed_at":"2026-08-12T18:59:54.103670Z","submitted_at":"2026-04-27T13:45:14Z","title":"GAMMAF: A Common Framework for Graph-Based Anomaly Monitoring Benchmarking in LLM Multi-Agent Systems","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T02:42:20.121207Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2604.24477"},"observation_digest":"sha256:43e997045bc4a08870543187d767cddbb5fad9816208b04e2aca78ee6e0a2183","observation_id":"33a197dd-4980-4503-ace5-b3db170b185e","resolution":{"observed_at":"2026-05-11T22:41:14.980522Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2605.05058","last_updated":"2026-05-06T15:53:17Z","snapshot_observed_at":"2026-07-06T23:17:43.402046Z","submitted_at":"2026-05-06T15:53:17Z","title":"SoK: Robustness in Large Language Models against Jailbreak Attacks","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-05-08T16:42:41.137808Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2605.05058"},"observation_digest":"sha256:74d39c18f27a26ad31877ec4651be867aeff898f0c89cc5e4aa097644fc5644a","observation_id":"e7e31ae5-7b21-4ec2-b77b-92152c3bf1b1","resolution":{"observed_at":"2026-05-11T18:01:08.809660Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2605.26409","last_updated":"2026-05-26T00:36:42Z","snapshot_observed_at":"2026-08-13T13:33:04.572065Z","submitted_at":"2026-05-26T00:36:42Z","title":"Jailbreak susceptibility prediction and mitigation via the behavioral geometry of models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-29T17:43:47.849960Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2605.26409"},"observation_digest":"sha256:e5d1e8911623bbe7f08dbee1332a6cbf59bedbd1af664feacbf68130ac49e55e","observation_id":"7d4cad6a-e56d-413b-b317-5a8a43f7c4f9","resolution":{"observed_at":"2026-06-29T17:53:47.691753Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2607.01277","last_updated":"2026-07-01T06:36:29Z","snapshot_observed_at":"2026-08-05T18:03:53.977353Z","submitted_at":"2026-07-01T06:36:29Z","title":"Cognitive Firewall: A Proactive, Zero-Trust, Multi-Gate Framework for LLM Safety","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-03T20:38:16.610310Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2607.01277"},"observation_digest":"sha256:7548ca7dba564cf7b9d5e2975a263612736d052f4b0511dda1b7052e9e4306f2","observation_id":"8334a1b7-c402-49a2-8f98-bc7ff2b7b8b5","resolution":{"observed_at":"2026-07-03T20:38:54.942955Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":"2403.04783","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-07-09T10:26:11.076263Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks","venue":"cs.LG","work_id":"2470c178-add6-463c-b04b-b4d405767b5d","year":2024},"citing_paper":{"arxiv_id":"2607.07461","last_updated":"2026-07-08T14:29:23Z","snapshot_observed_at":"2026-08-15T01:33:12.143322Z","submitted_at":"2026-07-08T14:29:23Z","title":"Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-07-09T10:22:23.782469Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2607.07461"},"observation_digest":"sha256:67c42f90db0d0bc14607b7c6845df0ce75ae13f06ddbd4e9e0d712b793366834","observation_id":"820b58bb-20bb-41c9-82a6-f5c7487c9d40","resolution":{"observed_at":"2026-07-09T10:26:11.077468Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-01T03:01:04.706186Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25255","last_updated":"2026-07-29T23:58:46Z","snapshot_observed_at":"2026-08-15T14:36:30.010999Z","submitted_at":"2026-07-28T03:55:47Z","title":"SafeFlow: Semantic Information-Flow Control for Blocking Malicious Propagation in Multi-Agent Systems","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-01T03:01:04.706186Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2607.25255"},"observation_digest":"sha256:b435ae39a1eaa5fc8205a8d643f4ce26790464d82e8893e342e74421f42aa0f5","observation_id":"df871845-a3d4-4bf0-a2d3-dd431ad15d7c","resolution":{"observed_at":"2026-08-01T03:01:04.706186Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-15T15:21:10.192438Z","title":"Autodefense: Multi-agent llm defense against jailbreak attacks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.00718","last_updated":"2026-08-01T15:35:58Z","snapshot_observed_at":"2026-08-16T04:35:15.613315Z","submitted_at":"2026-08-01T15:35:58Z","title":"Adversarial Attacks in Multi-Agent LLM Pipelines: Unveiling Structural Vulnerabilities in Agentic AI Architectures","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T15:21:10.192438Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2608.00718"},"observation_digest":"sha256:b910419b2cae52f25aae862a4a5d4605c05d7fa5eea5138ac4ee43e8558a4dbb","observation_id":"60b68910-3e3b-4683-ad27-bd0fb2648e82","resolution":{"observed_at":"2026-08-15T15:21:10.192438Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-15T15:17:24.164870Z","title":"arXiv:2403.04783","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.01085","last_updated":"2026-08-02T08:38:44Z","snapshot_observed_at":"2026-08-15T15:10:43.795197Z","submitted_at":"2026-08-02T08:38:44Z","title":"When Collaboration Becomes a Trigger: Collective Evidence-Threshold Backdoors in Multi-Agent Systems","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-15T15:17:24.164870Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2608.01085"},"observation_digest":"sha256:5a41d78cc13ab53cb620c24c0f69a1f5bc39c6ec173a9186bad6e89ddefe4553","observation_id":"335b71bd-8f04-476c-afdb-45d55c71fb06","resolution":{"observed_at":"2026-08-15T15:17:24.164870Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04783","snapshot_observed_at":"2026-08-15T14:21:42.711068Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.10530","last_updated":"2026-08-11T06:11:26Z","snapshot_observed_at":"2026-08-17T21:29:55.123485Z","submitted_at":"2026-08-11T06:11:26Z","title":"On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models","version":1},"reference_index":154,"source":"pdf_text","source_observed_at":"2026-08-15T14:21:42.711068Z"},"links":{"cited_paper":"/paper/2403.04783","citing_paper":"/paper/2608.10530"},"observation_digest":"sha256:6f1c9a09d988cb1f438a7feeadec16a6a5fbf03d06fcda649d2542c07f3f22e1","observation_id":"db108649-8481-473c-8799-452690224ebe","resolution":{"observed_at":"2026-08-15T14:21:42.711068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2403.04783/citation-record","integrity":"/paper/2403.04783/integrity","json":"/paper/2403.04783/citation-record.json","paper":"/paper/2403.04783"},"outbound":[],"paper":{"arxiv_id":"2403.04783","last_updated":"2024-11-14T18:14:00Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T06:55:39.053097Z","submitted_at":"2024-03-02T16:52:22Z","title":"AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2403.04783."}