{"as_of":"2026-08-13T23:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a37d229054b42cfa3a376118f28a65c1ad27af7e6b68996c49cba0fa9736292","coverage":[{"denominator":104,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T12:37:32.329030Z","state":"measured"},{"denominator":105,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":105,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-31T23:45:52.409766Z","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":"2026-07-08T02:44:27.670188Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"cited_work":{"arxiv_id":"2601.02295","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2601.02295","snapshot_observed_at":"2026-07-29T02:25:11.162934Z","title":"Cyclevla: Proactive self-correcting vision-language-action models via subtask backtracking and minimum bayes risk decoding.arXiv preprint arXiv:2601.02295, 2026","venue":null,"work_id":"8b49cf01-3abc-42c1-9664-3bf71b49f37d","year":2026},"citing_paper":{"arxiv_id":"2606.09740","last_updated":"2026-06-08T17:04:24Z","snapshot_observed_at":"2026-07-31T12:06:21.028418Z","submitted_at":"2026-06-08T17:04:24Z","title":"ProbeAct: Probe-Guided Training-Free Failure Recovery in Vision-Language-Action Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T16:33:12.726814Z"},"links":{"cited_paper":"/paper/2601.02295","citing_paper":"/paper/2606.09740"},"observation_digest":"sha256:fed00f0f0c3ab06b22aef93f89ff51eb12a37a3a324a5a8daaf71358f03a4d2a","observation_id":"2438ed09-6ee0-4afd-8803-180bbd334125","resolution":{"observed_at":"2026-07-29T02:25:11.162934Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"cited_work":{"arxiv_id":"2601.02295","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2601.02295","snapshot_observed_at":"2026-07-29T02:25:11.162934Z","title":"Cyclevla: Proactive self-correcting vision-language-action models via subtask backtracking and minimum bayes risk decoding.arXiv preprint arXiv:2601.02295, 2026","venue":null,"work_id":"8b49cf01-3abc-42c1-9664-3bf71b49f37d","year":2026},"citing_paper":{"arxiv_id":"2606.21386","last_updated":"2026-06-19T12:51:21Z","snapshot_observed_at":"2026-08-01T15:33:46.435054Z","submitted_at":"2026-06-19T12:51:21Z","title":"VLA-FAIL: Efficient Task Failure Detection for Finetuned Vision-Language-Action Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-26T14:57:41.592627Z"},"links":{"cited_paper":"/paper/2601.02295","citing_paper":"/paper/2606.21386"},"observation_digest":"sha256:600dde8b7f2279321eb4d42d6c0fb2de42535ed7b54966d6deeb7ce2ce39d0df","observation_id":"79e49fea-f65e-4e52-80f2-8b2a9735e27e","resolution":{"observed_at":"2026-07-29T02:25:11.162934Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"cited_work":{"arxiv_id":"2601.02295","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2601.02295","snapshot_observed_at":"2026-07-29T02:25:11.162934Z","title":"Cyclevla: Proactive self-correcting vision-language-action models via subtask backtracking and minimum bayes risk decoding.arXiv preprint arXiv:2601.02295, 2026","venue":null,"work_id":"8b49cf01-3abc-42c1-9664-3bf71b49f37d","year":2026},"citing_paper":{"arxiv_id":"2607.01212","last_updated":"2026-07-01T17:51:21Z","snapshot_observed_at":"2026-08-12T16:28:18.548460Z","submitted_at":"2026-07-01T17:51:21Z","title":"FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-02T10:50:11.153980Z"},"links":{"cited_paper":"/paper/2601.02295","citing_paper":"/paper/2607.01212"},"observation_digest":"sha256:74ff21111671734533926ee4a0e00e18be39c1e8e11d265abf4c8436a3f50a10","observation_id":"9e46eeef-0426-42a0-aac8-bb8ac2c9d781","resolution":{"observed_at":"2026-07-29T02:25:11.162934Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"cited_work":{"arxiv_id":"2601.02295","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2601.02295","snapshot_observed_at":"2026-07-29T02:25:11.162934Z","title":"Cyclevla: Proactive self-correcting vision-language-action models via subtask backtracking and minimum bayes risk decoding.arXiv preprint arXiv:2601.02295, 2026","venue":null,"work_id":"8b49cf01-3abc-42c1-9664-3bf71b49f37d","year":2026},"citing_paper":{"arxiv_id":"2607.06534","last_updated":"2026-07-13T03:52:19Z","snapshot_observed_at":"2026-07-16T23:18:47.677814Z","submitted_at":"2026-07-07T17:39:41Z","title":"CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-08T02:44:00.608590Z"},"links":{"cited_paper":"/paper/2601.02295","citing_paper":"/paper/2607.06534"},"observation_digest":"sha256:e926b70f59e88725b72af2d471e802fa0b8f6d074d12ea9f30d700aa4a6a894f","observation_id":"df713324-803e-446c-ba33-7525b4e3fe36","resolution":{"observed_at":"2026-07-29T02:25:11.162934Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.02295","snapshot_observed_at":"2026-07-31T23:45:52.409766Z","title":"Cyclevla: Proactive self-correcting vision-language-action models via subtask backtracking and minimum bayes risk decoding,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27881","last_updated":"2026-07-30T08:55:45Z","snapshot_observed_at":"2026-08-08T16:04:47.593576Z","submitted_at":"2026-07-30T08:55:45Z","title":"RoboBRIDGE: A Modular Framework for Bridging Policies to Robust Real-World Robotic Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-31T23:45:52.409766Z"},"links":{"cited_paper":"/paper/2601.02295","citing_paper":"/paper/2607.27881"},"observation_digest":"sha256:f6afd208968080f1b73416ae52e08885af71d7f3f9945d47a0fa5ec3cf00f1cf","observation_id":"58072049-ed52-4ebb-b37f-b7a51439cd98","resolution":{"observed_at":"2026-07-31T23:45:52.409766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2601.02295/citation-record","integrity":"/paper/2601.02295/integrity","json":"/paper/2601.02295/citation-record.json","paper":"/paper/2601.02295"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:37:22.864667Z","title":"When to ask for help: Proactive interventions in autonomous reinforcement learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:22.864667Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:27fcf426362c0178c1768823f0a69d7b3edda12dd3b29b098f9b555ffeb02df0","observation_id":"96f48573-c433-4c31-a281-849e42228fdb","resolution":{"observed_at":"2026-08-03T12:37:22.864667Z","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":"2026-08-03T12:37:22.953709Z","title":"Failure prediction with statistical guarantees for vision-based robot control,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:22.953709Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:d5c84e44d0d543deeab316437895a1d8b463d9de38d1cf79ad80c2f92c9b8285","observation_id":"ccda861d-95e4-49dc-8184-610fd8b1b4fd","resolution":{"observed_at":"2026-08-03T12:37:22.953709Z","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":"2026-08-03T12:37:23.061244Z","title":"Vision-language models as success detectors,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.061244Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f48819c58e47553118b238b1a0ceeabe424517ee1eab22a062f54e397c64f39f","observation_id":"1c435bde-f4fb-4b78-81c8-0ef6d09ae403","resolution":{"observed_at":"2026-08-03T12:37:23.061244Z","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":"2026-08-03T12:37:23.185112Z","title":"Asking for help: Failure prediction in behavioral cloning through value approximation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.185112Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:c6dd96d87bb908de0c7f16e521a3b06a4e00edbe982521f1d5b11a1af9b01ced","observation_id":"0a8f5214-31b0-48d5-b0b0-d28a85096fad","resolution":{"observed_at":"2026-08-03T12:37:23.185112Z","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":"2026-08-03T12:37:23.317551Z","title":"Unpacking failure modes of generative policies: Runtime monitoring of consistency and progress,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.317551Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:0858d51b3829c03300c883648c31cd9a891ce3b495fc63bef7278fc9c664aa69","observation_id":"655e1a2d-096e-4771-8523-100e285e6c8d","resolution":{"observed_at":"2026-08-03T12:37:23.317551Z","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":"2026-08-03T12:37:23.428232Z","title":"Grounding multimodal llms to embodied agents that ask for help with reinforcement learning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.428232Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f7da2c3fde4c5f90ec66771abf5a32d9b7e51df66df9e9b7aab5fe78c3f2d383","observation_id":"79164fe1-2548-49ff-90d4-6c00422129ea","resolution":{"observed_at":"2026-08-03T12:37:23.428232Z","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":"2026-08-03T12:37:23.569760Z","title":"Collabvla: Self-reflective vision-language-action model dreaming together with human,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.569760Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:5d6f2c1f239a2645b41b27394b7eef6307822b0a6a4fec0ada33bd9c37e5d17a","observation_id":"ef762909-3c6c-4489-8971-46511cb49a76","resolution":{"observed_at":"2026-08-03T12:37:23.569760Z","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":"2026-08-03T12:37:23.699365Z","title":"SAFE: multitask failure detection for vision-language- action models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.699365Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:2297870753c41b38ecf1e70d3962afe19382d4f35234736aa2213065380471a2","observation_id":"82631a19-59a6-4170-8b0b-1a15e8616e2c","resolution":{"observed_at":"2026-08-03T12:37:23.699365Z","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":"2026-08-03T12:37:23.760109Z","title":"REFLECT: summarizing robot experiences for failure explanation and correction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.760109Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:2d73759acb1cf767dd63b0607c8c6e2bc16068cee1949083116f080c64cab1f7","observation_id":"67001071-9029-4d53-9885-380c91798d56","resolution":{"observed_at":"2026-08-03T12:37:23.760109Z","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":"2026-08-03T12:37:23.869501Z","title":"AHA: A vision- language-model for detecting and reasoning over failures in robotic manipulation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.869501Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f4b70fec7e9f4daa6ffa6bdd41e8ac72c61033556b7e25ed819802a60e01461e","observation_id":"3c439392-90b9-4d5c-bdbe-9759227bb9e6","resolution":{"observed_at":"2026-08-03T12:37:23.869501Z","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":"2026-08-03T12:37:23.971198Z","title":"KitchenVLA: Iterative vision-language corrections for robotic execution of human tasks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:23.971198Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:30f65bd17186e19beddeef7cc6c33071abe76f6a6f9b1c8ad066f7a2d9e91a46","observation_id":"1cde713b-456c-4a88-a05a-c274a350b924","resolution":{"observed_at":"2026-08-03T12:37:23.971198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06060","last_updated":"2025-03-08T05:05:21Z","snapshot_observed_at":"2026-08-07T17:20:42.524747Z","submitted_at":"2025-03-08T05:05:21Z","title":"STAR: A Foundation Model-driven Framework for Robust Task Planning and Failure Recovery in Robotic Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06060","snapshot_observed_at":"2026-08-03T12:37:24.054453Z","title":"STAR: A foundation model-driven framework for robust task planning and failure recovery in robotic systems,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.054453Z"},"links":{"cited_paper":"/paper/2503.06060","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:3a8d95539279232dfb99d39a63d8aa88019f3ee1459a7ea4aed84d1a710dd105","observation_id":"ed39aa5b-d2de-46cb-8ad7-7366ba905e32","resolution":{"observed_at":"2026-08-03T12:37:24.054453Z","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":"2026-08-03T12:37:24.145374Z","title":"Openvla: An open-source vision-language-action model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.145374Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f97d973050b4282cacc0371b33c3cbe7179ae1b43aff782ea42fec82263bfbf8","observation_id":"4d06b377-2bd0-4655-b5ed-efa8e076c8fb","resolution":{"observed_at":"2026-08-03T12:37:24.145374Z","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":"2026-08-03T12:37:24.298121Z","title":"π0: A vision-language-action flow model for general robot control,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.298121Z"},"links":{"cited_paper":"/paper/2410.24164","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:431f1373d269bbe9ab775cfb8d3918a0ef985a3582b5c9cd173e8e3102484e7d","observation_id":"078e7b48-c4e7-4fdd-ab3b-7f8db8b30b2b","resolution":{"observed_at":"2026-08-03T12:37:24.298121Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14734","last_updated":"2025-03-27T02:52:43Z","snapshot_observed_at":"2026-08-02T04:15:31.100670Z","submitted_at":"2025-03-18T21:06:21Z","title":"GR00T N1: An Open Foundation Model for Generalist Humanoid Robots","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.14734","snapshot_observed_at":"2026-08-03T12:37:24.371572Z","title":"GR00T N1: an open foundation model for generalist humanoid robots,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.371572Z"},"links":{"cited_paper":"/paper/2503.14734","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:857196381a7a49ab80f29370c2323ecdf72eb04b1cd95d45863f0e0b5a35364a","observation_id":"815aa5bd-c3f8-494e-a2fc-25a6ab02e8c5","resolution":{"observed_at":"2026-08-03T12:37:24.371572Z","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":"2026-08-03T12:37:24.487678Z","title":"Policy adaptation via language optimization: Decomposing tasks for few-shot imitation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.487678Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:293fd3b1dd3acc0050835ca889d17ec57fd99ee00b5a682b1e7ee2c94d92355f","observation_id":"51d84c37-003a-417d-8320-3a1d8cb2da01","resolution":{"observed_at":"2026-08-03T12:37:24.487678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.16054","last_updated":"2025-04-22T17:31:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-22T17:31:29Z","title":"$\\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.16054","snapshot_observed_at":"2026-08-03T12:37:24.605491Z","title":"π0.5: a vision-language-action model with open-world generalization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.605491Z"},"links":{"cited_paper":"/paper/2504.16054","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:fb42bdab8a58f28824c02629f9cad121ef5858ed120818b6d1a6addf170357c3","observation_id":"5d3eeb53-4de4-49ff-9163-060000a59307","resolution":{"observed_at":"2026-08-03T12:37:24.605491Z","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":"2026-08-03T12:37:24.725101Z","title":"Hi robot: Open-ended instruction following with hierarchical vision-language-action models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.725101Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:7c0b50cd53d8f39e0ae3627fc6a91d11861baee2661c3ae274082733f4c2b4a4","observation_id":"99454dcb-ff29-4dda-a87e-4b7beabcaf7e","resolution":{"observed_at":"2026-08-03T12:37:24.725101Z","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":"2026-08-03T12:37:24.810205Z","title":"Seqvla: Sequential task execution for long-horizon manipulation with completion-aware vision- language-action model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.810205Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:a66427157f60006338e37eb191c7965fb51547f0e19af718914f649c8a4626b3","observation_id":"4d8e0e91-6c78-4c10-809b-a51bf2550e45","resolution":{"observed_at":"2026-08-03T12:37:24.810205Z","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":"2026-08-03T12:37:24.887046Z","title":"Long-vla: Unleashing long-horizon capability of vision language action model for robot manipulation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:24.887046Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:90d66ceed9c82592d573f09295f909eab2f95bc34e457a01d1e866d378e23591","observation_id":"2093ad69-9815-4508-9db8-7a151e05fa6e","resolution":{"observed_at":"2026-08-03T12:37:24.887046Z","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":"2026-08-03T12:37:25.085810Z","title":"Tactical rewind: Self-correction via backtracking in vision-and-language navigation,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:25.085810Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:7b891b4460fdbb44c901eab4f4ba8623d531d213f11cab50b402d605b980d98a","observation_id":"271fab47-90b6-4bd2-b194-61138e8992a7","resolution":{"observed_at":"2026-08-03T12:37:25.085810Z","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":"2026-08-03T12:37:25.262173Z","title":"Smartway: Enhanced waypoint prediction and backtracking for zero- shot vision-and-language navigation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:25.262173Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:34dea2bcb80b0301f124f2f916ec9127b910b169e585340a028451b90258c3b7","observation_id":"a3a5e0bd-a4b9-4f8f-b1ba-059d0c850fad","resolution":{"observed_at":"2026-08-03T12:37:25.262173Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.15917","last_updated":"2024-06-22T18:57:37Z","snapshot_observed_at":"2026-08-12T23:36:55.012185Z","submitted_at":"2024-06-22T18:57:37Z","title":"To Err is Robotic: Rapid Value-Based Trial-and-Error during Deployment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.15917","snapshot_observed_at":"2026-08-03T12:37:25.424813Z","title":"To err is robotic: Rapid value-based trial-and-error during deployment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:25.424813Z"},"links":{"cited_paper":"/paper/2406.15917","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:e19a475665e1224a671f43798eb2d47cdac1baa80a284919ae24714f490b6293","observation_id":"0a2c4195-af2c-42dd-b2a1-ddffdf74ec3f","resolution":{"observed_at":"2026-08-03T12:37:25.424813Z","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":"2026-08-13T17:20:44.002518Z","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":"2026-08-03T12:37:25.533473Z","title":"The llama 3 herd of models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:25.533473Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:a3c932a2d496e15c16a209c7ebc4ee76e279b6767062de45874f6f37acc0830c","observation_id":"c4a529fe-d812-40db-8539-4ed5cae8289b","resolution":{"observed_at":"2026-08-03T12:37:25.533473Z","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":"2026-08-03T12:37:25.648613Z","title":"Language models are few-shot learners,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:25.648613Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:c72b6eee17613647baa24bda6efb048461558e84f2b5480e74d8c367c5e18474","observation_id":"f88235a8-9b70-4c05-990f-17976cfa1d8a","resolution":{"observed_at":"2026-08-03T12:37:25.648613Z","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":"2026-08-03T12:37:25.776044Z","title":"Spatialpin: Enhancing spatial reasoning capabilities of vision-language models through prompting and interacting 3d priors,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:25.776044Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f86ee0e8c8abe87bd43140a0617a8d249f67b7adb4a34f4fa12c63882110b763","observation_id":"fa042d40-abe6-4ac5-a668-85bc52545051","resolution":{"observed_at":"2026-08-03T12:37:25.776044Z","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":"2026-08-03T12:37:25.913888Z","title":"Touch and go: Learning from human-collected vision and touch,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:25.913888Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:5c62ff7121c4ce0b748532f64d0d8650fc935d3fb21431c0db59c613d2ab210c","observation_id":"d93636d1-09b8-4bd6-be76-d5f4553d09ec","resolution":{"observed_at":"2026-08-03T12:37:25.913888Z","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":"2026-08-03T12:37:26.035947Z","title":"Improved baselines with visual instruction tuning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.035947Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:531784eb07f65c8ac9750ff056a2a0da24a701f7c068c459402fa474d29a508d","observation_id":"9d52b9b1-a4ef-4eea-b52e-6443080e9c3b","resolution":{"observed_at":"2026-08-03T12:37:26.035947Z","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":"2026-08-03T12:37:26.114491Z","title":"Minimum bayes-risk decoding for statistical machine translation,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.114491Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:5c78951091ef576ad9414c1ba3dc059881bb98e152d2978fd79c9f68cbce0a5a","observation_id":"ab1cd4d3-1510-49ae-b69a-21ef4dc34909","resolution":{"observed_at":"2026-08-03T12:37:26.114491Z","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":"2026-08-03T12:37:26.201978Z","title":"Open x-embodiment: Robotic learning datasets and RT-X models : Open x-embodiment collaboration,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.201978Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:4f01eaa62e80d229532da3489b67911765076204a7dd5cb9d04eb1719af03f88","observation_id":"a1c5f06e-d6db-43d4-a858-1e28ddb12a16","resolution":{"observed_at":"2026-08-03T12:37:26.201978Z","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":"2026-08-03T12:37:26.369692Z","title":"RDT-1B: a diffusion foundation model for bimanual manip- ulation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.369692Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:770c79971d7275ccea1d0279db476b626c26d6bf1bfe5988027cff3184007d13","observation_id":"16eea73a-f9e1-4201-98c3-2d480f7a9844","resolution":{"observed_at":"2026-08-03T12:37:26.369692Z","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":"2026-08-03T12:37:26.520585Z","title":"Robomonkey: Scaling test-time sampling and veri- fication for vision-language-action models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.520585Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:ddf5fbafa60c215083ff6cb8e42fcb8930734121635d26649694607b65f23977","observation_id":"976c9c12-aeab-4702-ab6d-c72d38a3c96b","resolution":{"observed_at":"2026-08-03T12:37:26.520585Z","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":"2026-08-03T12:37:26.646009Z","title":"Rover: Robot reward model as test-time verifier for vision- language-action model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.646009Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:d14415569c61edbbc84301f0c8307cfc31c97616ffa483444d30ee04b575e83e","observation_id":"ee316041-b288-4ee6-b8be-d3535732d5c9","resolution":{"observed_at":"2026-08-03T12:37:26.646009Z","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":"2026-08-03T12:37:26.737561Z","title":"Sampling-based approximations to minimum bayes risk decoding for neural machine translation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.737561Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:79b3e2871d8de6f86659e463fee93b1e89f710a934467f8a443fb16aa5d45960","observation_id":"524dfbd5-fb45-429f-a8db-f3a49ba13001","resolution":{"observed_at":"2026-08-03T12:37:26.737561Z","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":"2026-08-03T12:37:26.872170Z","title":"On extending direct preference optimization to accommodate ties,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.872170Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:00fc68b2a3a5bc46b3cfb7c631475ff489e163406fad9212484783afd964a0ec","observation_id":"a92712b9-f722-4f6a-a88f-44a1cb779766","resolution":{"observed_at":"2026-08-03T12:37:26.872170Z","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":"2026-08-03T12:37:26.987996Z","title":"Direct preference optimization for neural machine translation with minimum bayes risk decoding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:26.987996Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:a0ebf560e4e3c37e9c92e44cbfaa07a45a7950de729c1e2173d49fab15292ca9","observation_id":"0fb963ff-24c1-4edd-be22-d575d2551317","resolution":{"observed_at":"2026-08-03T12:37:26.987996Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.08558","last_updated":"2025-06-20T05:51:24Z","snapshot_observed_at":"2026-08-13T18:44:40.463152Z","submitted_at":"2025-03-11T15:47:12Z","title":"Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.08558","snapshot_observed_at":"2026-08-03T12:37:27.032739Z","title":"Can we detect failures without failure data? uncertainty-aware runtime failure detection for imitation learning policies,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.032739Z"},"links":{"cited_paper":"/paper/2503.08558","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:b371898e3e242c7d900272fb99dd485a049faf3ef408ed14cc5f02439e7ee8c6","observation_id":"705bcd79-6b3b-4464-8987-ad77eba0a37a","resolution":{"observed_at":"2026-08-03T12:37:27.032739Z","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":"2026-08-03T12:37:27.105629Z","title":"Sparse and complete latent organization for geospatial semantic segmentation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.105629Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:cd9182ac813d292b286feb7fbc56def078d8bf6d8724a6b954327ec341b9f043","observation_id":"98337625-6bd8-4b96-be8e-a0e5d2eb1a75","resolution":{"observed_at":"2026-08-03T12:37:27.105629Z","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":"2026-08-03T12:37:27.157681Z","title":"Error-aware imitation learning from teleopera- tion data for mobile manipulation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.157681Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:024f6704573be49f319e6449616bcc49c18ec71fd0e3285ef968898366924abd","observation_id":"8ec3bd44-8ef5-4001-969d-ae72b918ffbd","resolution":{"observed_at":"2026-08-03T12:37:27.157681Z","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":"2026-08-03T12:37:27.225844Z","title":"Model-based runtime monitoring with interactive imitation learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.225844Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:4e3fb81dc416e879ce9e1f1fc55f0c59973ba9fc3cad570adf86f750e60524ec","observation_id":"aa9cf348-b02b-4ed3-98bf-11b912367380","resolution":{"observed_at":"2026-08-03T12:37:27.225844Z","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":"2026-08-03T12:37:27.333690Z","title":"Real-time anomaly detection and reactive planning with large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.333690Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:242eb32839ea224276ee65cc770c099daed3456e000269604d50cda58fb420c1","observation_id":"0e7b5b6a-ae50-4d31-b72f-192b3c3392df","resolution":{"observed_at":"2026-08-03T12:37:27.333690Z","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":"2026-08-03T12:37:27.426730Z","title":"Doremi: Grounding language model by detecting and recovering from plan-execution misalignment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.426730Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:802c5762ffc7f6ea461a3e8dbd4ecdf0aded8f086241717bb96d8c2c989c9853","observation_id":"a21f5357-0cb7-4a1e-b18d-aae771efba03","resolution":{"observed_at":"2026-08-03T12:37:27.426730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.17418","last_updated":"2025-03-19T03:55:48Z","snapshot_observed_at":"2026-08-12T23:56:51.467364Z","submitted_at":"2024-05-27T17:58:48Z","title":"A Self-Correcting Vision-Language-Action Model for Fast and Slow System Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.17418","snapshot_observed_at":"2026-08-03T12:37:27.492757Z","title":"A self-correcting vision-language- action model for fast and slow system manipulation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.492757Z"},"links":{"cited_paper":"/paper/2405.17418","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:0068e2b280f7095f3b6086f8f999e9e19e303b9fd0529d8ef3507229daf07b78","observation_id":"f6d0d885-b373-4912-8df6-9478e458394b","resolution":{"observed_at":"2026-08-03T12:37:27.492757Z","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":"2026-08-03T12:37:27.596185Z","title":"Coopera: Continual open-ended human-robot assistance,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.596185Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:93f9dd6b626cc54220038acf98810cdd945c0ed62d3a067fecae5825f4cea10f","observation_id":"e019a7b2-47ce-4726-9d2d-3aeecdf827df","resolution":{"observed_at":"2026-08-03T12:37:27.596185Z","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":"2026-08-03T12:37:27.706608Z","title":"Multi-task interactive robot fleet learning with visual world models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.706608Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:addc907d0e8659930464c675815912ab11f700103c5083cf5ad5ae59263c0025","observation_id":"9ce73146-8ceb-4c0e-9a88-df5f5ecf1c66","resolution":{"observed_at":"2026-08-03T12:37:27.706608Z","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":"2026-08-03T12:37:27.779470Z","title":"Cot-vla: Visual chain-of-thought reasoning for vision-language-action models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.779470Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:bbc3f3c410834f091737fe483de0e2ec92f8189e94150ac2587e4a86827078e9","observation_id":"a1e96a8a-6849-488d-8b6e-afb9db4c2b8b","resolution":{"observed_at":"2026-08-03T12:37:27.779470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.16707","last_updated":"2025-02-23T20:42:15Z","snapshot_observed_at":"2026-08-11T01:14:45.608554Z","submitted_at":"2025-02-23T20:42:15Z","title":"Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.16707","snapshot_observed_at":"2026-08-03T12:37:27.872949Z","title":"Reflective planning: Vision-language models for multi-stage long-horizon robotic manipulation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.872949Z"},"links":{"cited_paper":"/paper/2502.16707","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:fced58ea25f3112ee881af2e62885273fb131aa291711dbb5f7ea14c421cc0b5","observation_id":"da86f2f4-a9b6-4b5c-8c55-9474ab349eaf","resolution":{"observed_at":"2026-08-03T12:37:27.872949Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09985","last_updated":"2025-06-11T17:57:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-11T17:57:09Z","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.09985","snapshot_observed_at":"2026-08-03T12:37:27.943411Z","title":"V-JEPA 2: Self-supervised video models enable understanding, prediction and planning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:27.943411Z"},"links":{"cited_paper":"/paper/2506.09985","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:037e8b35871abbc71cc08665fdd295f048cb902b3120fcaf4ec769b08da1a1ef","observation_id":"8bc65591-6b88-4c89-bb64-14a49b14b01e","resolution":{"observed_at":"2026-08-03T12:37:27.943411Z","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":"2026-08-03T12:37:28.031346Z","title":"Dexvla: Vision- language model with plug-in diffusion expert for general robot control,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.031346Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:455100d2a136f5e12dccda7b2b0778682b657f12bcec996d01539463b18e7cb6","observation_id":"c3bda5fc-c336-4bdd-9ab7-3ba3d20f00b8","resolution":{"observed_at":"2026-08-03T12:37:28.031346Z","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":"2026-08-03T12:37:28.136773Z","title":"RDD: retrieval-based demon- stration decomposer for planner alignment in long-horizon tasks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.136773Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:936dd847e7a3fb6b4de3b31391e37f38e2a4cbf4071d3c6fb9cc2af636e8468d","observation_id":"73daf7b2-729a-466c-8479-517b2077b1b2","resolution":{"observed_at":"2026-08-03T12:37:28.136773Z","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":"2026-08-03T12:37:28.209976Z","title":"Robotic control via embodied chain-of-thought reasoning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.209976Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:4bea73b474ee95709a1b6e328cdd37938866c1e98677d030c77a3b006041d511","observation_id":"9a1b8050-a274-4180-bfc6-f6028450e9bd","resolution":{"observed_at":"2026-08-03T12:37:28.209976Z","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":"2026-08-03T12:37:28.283583Z","title":"Chatvla: Unified multimodal understanding and robot control with vision-language-action model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.283583Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:ee16b9052bae4394c7bd2881a246cf34acbe3063e425cbe6380140c9415a006a","observation_id":"fc0c5f7c-7bd3-4a95-ba2c-42dae6313373","resolution":{"observed_at":"2026-08-03T12:37:28.283583Z","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":"2026-08-03T12:37:28.345828Z","title":"Chatvla-2: Vision- language-action model with open-world embodied reasoning from pretrained knowledge,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.345828Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:1a3cac6246e44f2a8bcaecedbda1317e02d73289fb3f7affc467682208b4fa8c","observation_id":"79570ca6-6242-4afd-b246-3b907d6d36e9","resolution":{"observed_at":"2026-08-03T12:37:28.345828Z","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":"2026-08-03T12:37:28.427720Z","title":"Training strategies for efficient embodied reasoning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.427720Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:d3a5b36fa63fc3896ba13f228e8c9a277b6393857ab11430d6d8b5b40731003c","observation_id":"ea16e8f3-8e4b-49ae-b335-dc2b028b125a","resolution":{"observed_at":"2026-08-03T12:37:28.427720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.00062","last_updated":"2026-02-24T21:52:50Z","snapshot_observed_at":"2026-07-06T22:34:38.619949Z","submitted_at":"2025-10-28T22:44:13Z","title":"World Simulation with Video Foundation Models for Physical AI","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.00062","snapshot_observed_at":"2026-08-03T12:37:28.494262Z","title":"World simulation with video foundation models for physical ai,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.494262Z"},"links":{"cited_paper":"/paper/2511.00062","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:5ab92dd4b2e474896404fe33c17785df9a95dd72ad5f7a373f8794fb716a3085","observation_id":"0110820c-4239-499e-a7bd-9fce4a723f27","resolution":{"observed_at":"2026-08-03T12:37:28.494262Z","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":"2026-08-03T12:37:28.604796Z","title":"Run-time observation interventions make vision-language-action models more visually robust,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.604796Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:561268269bda0314e8169165b34e206f1c27636e3a017e8dad905fd272ec3936","observation_id":"1eb593a2-43c0-4761-a5df-1ddf8e9c6f03","resolution":{"observed_at":"2026-08-03T12:37:28.604796Z","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":"2026-08-03T12:37:28.658649Z","title":"IA-VLA: input augmentation for vision-language-action models in settings with semantically complex tasks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.658649Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:311a698a33a831dfe2622f8cc659a6c63e83dd6fa3cb35fc0c71be40d4b58af7","observation_id":"41ca8958-0f7c-4feb-b1a0-d1f785f762f8","resolution":{"observed_at":"2026-08-03T12:37:28.658649Z","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":"2026-08-03T12:37:28.735440Z","title":"Visual prompting via image inpainting,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.735440Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:41302c597cc895d30bdf7fb15d5c8a41156f191a9bfdcac4a5a4d67e64cf8347","observation_id":"784584c4-eb2f-4f1f-9d40-1459397462fc","resolution":{"observed_at":"2026-08-03T12:37:28.735440Z","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":"2026-08-03T12:37:28.824172Z","title":"Scaling LLM test-time compute optimally can be more effective than scaling model parameters,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.824172Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:d301b994166c35daf7295df1de67fd97cf7cb76b9fc8702fdc1e66b2342ebaf4","observation_id":"22945ce7-6fd1-4ad1-8d47-23e65e959c48","resolution":{"observed_at":"2026-08-03T12:37:28.824172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-13T15:58:13.809876Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-03T12:37:28.878438Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.878438Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:481c8792274e75b278687ce4c93ad274b86bd548a86ddae14b525c5c98ec4bda","observation_id":"e8d7d9e5-ee13-4185-ace0-9db6fc21e592","resolution":{"observed_at":"2026-08-03T12:37:28.878438Z","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":"2026-08-03T12:37:28.971371Z","title":"Introducing openai o3 and o4-mini,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:28.971371Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:53485ec6dd305e283a8cf675a05cb43b951f2b214eb14f541403f4d4fe28bb0b","observation_id":"8919c781-7dd2-475d-abb2-17aaeda0d1af","resolution":{"observed_at":"2026-08-03T12:37:28.971371Z","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":"2026-08-03T12:37:29.035874Z","title":"Steering your generalists: Improving robotic foundation models via value guidance,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.035874Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:11d68b2641b9c5422dac0cd5b3002ef04f3edba7240ac093e663fcc8b7377478","observation_id":"2f4b63f3-7cf5-4162-bbab-9aa18fca234d","resolution":{"observed_at":"2026-08-03T12:37:29.035874Z","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":"2026-08-03T12:37:29.131212Z","title":"Navid: Video-based VLM plans the next step for vision-and-language navigation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.131212Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:bf8f9370a0758f3ffef00e6d0ccb32ec2ee81c0e9eeaab4fa355a6e580f6ccdc","observation_id":"c5f82710-3f22-4662-baea-5ecf408120c3","resolution":{"observed_at":"2026-08-03T12:37:29.131212Z","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":"2026-08-03T12:37:29.205893Z","title":"Chain-of-thought prompting elicits reasoning in large language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.205893Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:45520f05a892c8657f0cbfd533b2a1b5fcc094140de4c66e1f8cfb13561e9150","observation_id":"d9a2b2f8-5784-477c-8ea3-819f69c592ea","resolution":{"observed_at":"2026-08-03T12:37:29.205893Z","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":"2026-08-03T12:37:29.278433Z","title":"Introducing gpt-4.1 in the api,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.278433Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:8cddba1d1b1628d6f7235ac55d74243e03ba9223aa0a17d681bed559b757a9da","observation_id":"0e5c60f0-8c0e-4b38-9e20-e1494264d24d","resolution":{"observed_at":"2026-08-03T12:37:29.278433Z","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":"2026-08-03T12:37:29.348086Z","title":"Fine-tuning vision-language-action models: Optimizing speed and success,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.348086Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:a797c8289873ca7b4488d4f0757920b682ccff9390a3cd98cfec02eb4ec9eaae","observation_id":"fa34edf2-392f-4d1b-85f4-e60a579a3c5a","resolution":{"observed_at":"2026-08-03T12:37:29.348086Z","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":"2026-08-03T12:37:29.452465Z","title":"Introducing gpt-5.2,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.452465Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:92e4e6cbd7abb3c0792520575ec6cbd6a1531c5676f7ec4c48b29f69102120d2","observation_id":"d3bee82f-4be7-426c-9702-cdd3972c046d","resolution":{"observed_at":"2026-08-03T12:37:29.452465Z","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":"2026-08-03T12:37:29.530462Z","title":"LIBERO: benchmarking knowledge transfer for lifelong robot learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.530462Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:fa6244119b35a60a1782044c64fc437bfcc22ea8ff06be3bec59e1b16803287d","observation_id":"3fd9eff5-7866-4cb7-b24f-231e4b7a66d0","resolution":{"observed_at":"2026-08-03T12:37:29.530462Z","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":"2026-08-03T12:37:29.577126Z","title":"Tracevla: Visual trace prompting enhances spatial- temporal awareness for generalist robotic policies,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.577126Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:9524f9f08639499aea5ef1a5b03c6a05124799c45beb6b6d6aa4c7a1fed734da","observation_id":"7bb66f5c-50b7-4dfe-9d75-ba55a97de23f","resolution":{"observed_at":"2026-08-03T12:37:29.577126Z","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":"2026-08-03T12:37:29.673550Z","title":"Thinkact: Vision-language-action reasoning via reinforced visual latent planning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.673550Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:2966b9b33e6899bbdcf54e754f3120c3815004fde86eeae095cbf882d9f1c3de","observation_id":"055c64ed-8d24-416a-931c-29fe51fed4a1","resolution":{"observed_at":"2026-08-03T12:37:29.673550Z","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":"2026-08-03T12:37:29.729978Z","title":"FPC-VLA: A vision-language-action framework with a supervisor for failure prediction and correction,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.729978Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f2010c97156c47e2bde96eadd59b2ddc6b975082ab60d4e0e3cb3dcfe9412422","observation_id":"3a33e743-9a3b-4e4c-ba36-40f2af890710","resolution":{"observed_at":"2026-08-03T12:37:29.729978Z","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":"2026-08-03T12:37:29.848740Z","title":"Cogvla: Cognition- aligned vision-language-action model via instruction-driven routing & sparsification,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.848740Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:804b96f3a67f5593e9cb0cd3d078c257a354a4e605497c2d10c86fd26522bd39","observation_id":"572daf2e-c3a1-4903-9f83-8fe46e8b0f9c","resolution":{"observed_at":"2026-08-03T12:37:29.848740Z","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":"2026-08-03T12:37:29.944298Z","title":"Diffusion policy: Visuomotor policy learning via action diffusion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:29.944298Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:5672e13c07817dcd5b853aa9316ad11b6250061f4241ada18cf93f10b936a8ea","observation_id":"f53e2420-78a8-4a23-bc9f-cb973236383f","resolution":{"observed_at":"2026-08-03T12:37:29.944298Z","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":"2026-08-03T12:37:30.051375Z","title":"Octo: An open-source generalist robot policy,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.051375Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:6ba3bb12aa3f97948e0aa86251b9fe2a2aeabbdd499a1aa98496f45c17759016","observation_id":"5454ef12-cc56-4385-836e-8577b5334fcd","resolution":{"observed_at":"2026-08-03T12:37:30.051375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.15830","last_updated":"2025-05-19T02:40:18Z","snapshot_observed_at":"2026-07-06T20:26:31.558337Z","submitted_at":"2025-01-27T07:34:33Z","title":"SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.15830","snapshot_observed_at":"2026-08-03T12:37:30.141155Z","title":"Spatialvla: Exploring spatial representations for visual-language-action model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.141155Z"},"links":{"cited_paper":"/paper/2501.15830","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:9a35d38e294edb7a46706474415a043abbf09c987146a724b1b0de121170143a","observation_id":"28b38013-8abc-4b3f-ac25-e05d26b0bbb5","resolution":{"observed_at":"2026-08-03T12:37:30.141155Z","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":"2026-08-03T12:37:30.219438Z","title":"Improving minimum bayes risk decoding with multi-prompt,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.219438Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f67da267f6325f61cee8bcea120aebd1326072ad6d157bd71563060f596a5d9e","observation_id":"44e5489d-70ec-486b-bd33-3ad2a84c938f","resolution":{"observed_at":"2026-08-03T12:37:30.219438Z","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":"2026-08-03T12:37:30.316296Z","title":"Fast best-of-n decoding via speculative rejection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.316296Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:b62bf44e3cf8c96a1007ed9c875110263dcffaa3f9d4b5a1fca44c3640c995f6","observation_id":"b95f13bb-22ee-4505-8876-e0811f4b0a74","resolution":{"observed_at":"2026-08-03T12:37:30.316296Z","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":"2026-08-03T12:37:30.405851Z","title":"Towards understanding sycophancy in language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.405851Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:31047a52ef6782e69c82c27e659d450a692533f50c814bb1276362d960ce59ff","observation_id":"3f20722c-c7af-4680-b66b-0a9f92b36a15","resolution":{"observed_at":"2026-08-03T12:37:30.405851Z","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":"2026-08-03T12:37:30.492554Z","title":"Efficient vertical federated learning with secure aggregation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.492554Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:8816e18497303fd22263b18c1e52bbb9636b7f85f11daef3a57a6d12ea34f3dd","observation_id":"7f956d87-2542-44b9-8373-ce1a52e94c01","resolution":{"observed_at":"2026-08-03T12:37:30.492554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16794","last_updated":"2024-02-17T19:56:06Z","snapshot_observed_at":"2026-08-13T11:32:36.917685Z","submitted_at":"2023-05-26T10:17:36Z","title":"Secure Vertical Federated Learning Under Unreliable Connectivity","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16794","snapshot_observed_at":"2026-08-03T12:37:30.560341Z","title":"vfedsec: Efficient secure aggregation for vertical federated learning via secure layer,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.560341Z"},"links":{"cited_paper":"/paper/2305.16794","citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:f8430afaee8609f10320a38831d2742b204e3d1d11c37cf2e7239dbf08925b7f","observation_id":"5a993248-9e0e-48b9-bd47-ee029d48d2a3","resolution":{"observed_at":"2026-08-03T12:37:30.560341Z","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":"2026-08-03T12:37:30.660086Z","title":"Gradient-less federated gradient boosting tree with learnable learning rates,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.660086Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:706fc87ffc8e94a44fec816bb12b4ccbfd204bd24f5f12dec4254f2342bdd234","observation_id":"1b63b4a6-8f29-4aa8-bff7-aa81908a9277","resolution":{"observed_at":"2026-08-03T12:37:30.660086Z","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":"2026-08-03T12:37:30.732695Z","title":"Your job is to decompose this task into a minimal set of formal subtasks that a robot must perform to complete the task","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.732695Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:d46c1654bb913339ee0d5ae778a8e246ec896122d1a83ff6efe6f732649ece8a","observation_id":"f8d29124-54ce-4de8-b058-04db42b27004","resolution":{"observed_at":"2026-08-03T12:37:30.732695Z","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":"2026-08-03T12:37:30.819788Z","title":"- Do not over-decompose — prefer atomic but essential steps","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.819788Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:0a20535bd237ce3658bd8d99fcf2cc62c391ccb16c4fed923a2ca75dfc1c449d","observation_id":"c8d82d51-2c49-4511-800f-4a9d02311da7","resolution":{"observed_at":"2026-08-03T12:37:30.819788Z","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":"2026-08-03T12:37:30.917604Z","title":"- Mention relative spatial cues (e.g., above the drawer handle) if implied in the task","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:30.917604Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:263ddee618852248409804fd6d2fa0cf5d0647c636359cc932cf3a2921328401","observation_id":"43217c1d-48ad-4339-9b7b-6c4ffc1b8ac4","resolution":{"observed_at":"2026-08-03T12:37:30.917604Z","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":"2026-08-03T12:37:31.041180Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.041180Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:1000151691b2e82c93969072cb2885265e97424d5ed64ea91a2771b222e54267","observation_id":"a9b8fd7e-930b-40bc-8d85-52990a4912ae","resolution":{"observed_at":"2026-08-03T12:37:31.041180Z","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":"2026-08-03T12:37:31.145739Z","title":"Move the gripper","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.145739Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:c636547ca76f5402f27bec0b44731bd10ed6dfd3f71b95a78ff68c4a711aab08","observation_id":"97f68db3-8caf-4a1f-9a96-e6a49e343b4d","resolution":{"observed_at":"2026-08-03T12:37:31.145739Z","resolver_source":null,"status":"parse_uncertain"},"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":"2026-08-03T12:37:31.272796Z","title":"Rotate the gripper","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.272796Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:b24546651bc2600ebb429e4412dcdebf06f45fb012011b9c424b0bdadbeb9afd","observation_id":"43e02d42-1bb8-4695-b63c-41ff34ad04e1","resolution":{"observed_at":"2026-08-03T12:37:31.272796Z","resolver_source":null,"status":"parse_uncertain"},"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":"2026-08-03T12:37:31.388317Z","title":"Open the gripper","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.388317Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:004306d8778ed10565f225a71f0b6b9c2d00cb917fa3cc139a892674ed2449e9","observation_id":"4ba08915-aab7-4458-b303-d47a51fb2d48","resolution":{"observed_at":"2026-08-03T12:37:31.388317Z","resolver_source":null,"status":"parse_uncertain"},"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":"2026-08-03T12:37:31.466096Z","title":"Close the gripper","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.466096Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:ff68f115cbd66c9ed1409719cb1292b631627f1d520ef8b02631a3b83c80b1e7","observation_id":"490e826d-9011-49b0-ad71-bf810ba0b656","resolution":{"observed_at":"2026-08-03T12:37:31.466096Z","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":"2026-08-03T12:37:31.626639Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.626639Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:4d53044fed2dca9884ddbad817fc20e41a1b998d196602bb89ef6c2a5ed4e676","observation_id":"d837681f-1bed-410a-b039-0a9e7e22c822","resolution":{"observed_at":"2026-08-03T12:37:31.626639Z","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":"2026-08-03T12:37:31.736829Z","title":"<subtask_1>","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.736829Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:8271c6842515aec3d5c927d884114737eacb1fa278e6d8b7d6e678a23e2e2c6f","observation_id":"b0e78d67-27e4-4b8d-a1c9-ac84e1ca44fb","resolution":{"observed_at":"2026-08-03T12:37:31.736829Z","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":"2026-08-03T12:37:31.810453Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.810453Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:733205c59959b5f331a9268d1ade87c93653d20733e7bfce6a57d9c76c38e095","observation_id":"9a3a0885-53b5-44fe-9cc0-f45f39d3680e","resolution":{"observed_at":"2026-08-03T12:37:31.810453Z","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":"2026-08-03T12:37:31.866325Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.866325Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:619f7d1fa532c1e4948ea34617643ef9db75a78760ad16e9f08d039c72b3e19a","observation_id":"36ae27db-7996-42b0-a268-8e616802f3dd","resolution":{"observed_at":"2026-08-03T12:37:31.866325Z","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":"2026-08-03T12:37:31.952350Z","title":"<move_primitive>","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:31.952350Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:e0215bc5b25462bd32c639e9a8329f7fa624d6dc6dde33811137066d556ac604","observation_id":"1a8eb945-c468-40d2-8caf-ed906ebb862c","resolution":{"observed_at":"2026-08-03T12:37:31.952350Z","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":"2026-08-03T12:37:32.049612Z","title":"stop\" labels often appear even when the robot is still moving. - Treat","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:32.049612Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:c72ca700d3efe846ddbc88429bc4d73ee6e737c09076f6d69f526ab6cd54ea8c","observation_id":"1fa496b7-1de5-4282-9556-a0f1da430c09","resolution":{"observed_at":"2026-08-03T12:37:32.049612Z","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":"2026-08-03T12:37:32.102052Z","title":"- Cross-reference other movement labels to decide whether a short-duration label is meaningful or just noise","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:32.102052Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:ed395a6176e8b9d6f40db96981f3fa38df72c5f045d965164786ee194836921b","observation_id":"c296860a-c3b6-4b0b-bbad-b739248671ef","resolution":{"observed_at":"2026-08-03T12:37:32.102052Z","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":"2026-08-03T12:37:32.153940Z","title":"subtask_1","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:32.153940Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:7906b277165b6680d4eae13ce22c279e1b55f5c60e8ca1817a96a4e81a41434c","observation_id":"0968f3fc-d5e7-46f5-97f2-05fcdaf85c58","resolution":{"observed_at":"2026-08-03T12:37:32.153940Z","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":"2026-08-03T12:37:32.214810Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:32.214810Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:bf7c8a653a183961817cabb28a160762cf2e23f592028447ea8918efc81ca8ab","observation_id":"bd99d636-2adb-45fa-94c0-0d40399750c4","resolution":{"observed_at":"2026-08-03T12:37:32.214810Z","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":"2026-08-03T12:37:32.272008Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:32.272008Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:947aab9b881c6ee028a39dde008e754790853b252a77029f1b0d6a0cffb6b8c9","observation_id":"1f2514c3-297e-490f-9044-a42030568759","resolution":{"observed_at":"2026-08-03T12:37:32.272008Z","resolver_source":null,"status":"parse_uncertain"},"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":"2026-08-03T12:37:32.329030Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding","version":2},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-03T12:37:32.329030Z"},"links":{"citing_paper":"/paper/2601.02295"},"observation_digest":"sha256:21341bac6a8a90c035ae7c7b6bbeede873f95b69b4af22451552169b6ffdf59e","observation_id":"0f741211-7a2d-4cea-bdbf-2d1ab16e1e54","resolution":{"observed_at":"2026-08-03T12:37:32.329030Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2601.02295","last_updated":"2026-07-28T17:46:45Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-08T16:04:20.785264Z","submitted_at":"2026-01-05T17:31:01Z","title":"CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":4,"unresolved":96,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":104},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 100 of 104 outbound references and 5 inbound Pith citation observations for arXiv:2601.02295."}