{"as_of":"2026-08-18T19:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:382a5d0c3f4ca44311796606877d4e2711b67492606fb3c5d4e22ce15c2892b3","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T12:59:13.709099Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-29T17:34:41.053725Z","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":"2026-06-29T18:03:48.642678Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"cited_work":{"arxiv_id":"2412.13662","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.13662","snapshot_observed_at":"2026-06-29T18:03:48.642678Z","title":null,"venue":null,"work_id":"2abd9c53-3b84-45ce-b0be-1f36753ceb64","year":2024},"citing_paper":{"arxiv_id":"2605.26478","last_updated":"2026-05-26T02:35:08Z","snapshot_observed_at":"2026-08-12T14:23:50.664257Z","submitted_at":"2026-05-26T02:35:08Z","title":"Efficient On-policy Visual-RL via Stochastic Decoupled Policy Gradient","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-29T17:34:41.053725Z"},"links":{"cited_paper":"/paper/2412.13662","citing_paper":"/paper/2605.26478"},"observation_digest":"sha256:747b392d7ba117da91871f357ef772bd9d2c4f4a32ace256414a3b8b21a0b437","observation_id":"df26891e-72b7-4040-8c34-9873abd65404","resolution":{"observed_at":"2026-06-29T18:03:48.643919Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.13662/citation-record","integrity":"/paper/2412.13662/integrity","json":"/paper/2412.13662/citation-record.json","paper":"/paper/2412.13662"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.545402Z","title":", \" * write output.state after.block = add.period write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.545402Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:67d799e7202c57171dfec53b4f6c40d4504870c59569a0f6ccda59ea633882d3","observation_id":"5ace8c56-7be9-45b5-9c62-4a659618414a","resolution":{"observed_at":"2026-08-11T12:59:13.545402Z","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":"2026-08-11T12:59:13.549886Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.549886Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:58cc36454359dfd5692474b07e25700c822d0688656edf18c14a5eb2aa635b6d","observation_id":"5c351590-0d5f-47ae-912f-e75a224b7dbf","resolution":{"observed_at":"2026-08-11T12:59:13.549886Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.07113","last_updated":"2019-10-16T00:59:05Z","snapshot_observed_at":"2026-08-02T15:37:37.200292Z","submitted_at":"2019-10-16T00:59:05Z","title":"Solving Rubik's Cube with a Robot Hand","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.07113","snapshot_observed_at":"2026-08-11T12:59:13.554015Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.554015Z"},"links":{"cited_paper":"/paper/1910.07113","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:43156a7ea71c774a25fab19e70bc08de7b1a0c48e5b3b11a2ed6444e9cd2408f","observation_id":"4b3b76d6-1b28-4846-b531-80a5486cfbc0","resolution":{"observed_at":"2026-08-11T12:59:13.554015Z","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":"2026-08-11T12:59:13.558800Z","title":"M.; Baker, B.; Chociej, M.; Jozefowicz, R.; McGrew, B.; Pachocki, J.; Petron, A.; Plappert, M.; Powell, G.; Ray, A.; et al","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.558800Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:f6a7497970a29cc3ebe9e1246f7cfad42c7bd6c9dc42e94087f81a1875ff6ad5","observation_id":"c27aed0d-09d1-47e0-bd6b-9c28452561d7","resolution":{"observed_at":"2026-08-11T12:59:13.558800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.159390Z","title":null,"venue":null,"work_id":"2669e869-f6a3-4c6d-ac69-bcc5bbac88a1","year":2015},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.563505Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:ae499b391a97224c8eb8cfa9a65f742cc8957c2fc20a01df9a5de4c8141a6c52","observation_id":"68897725-5b63-4771-ae7f-4ba02958c816","resolution":{"observed_at":"2026-08-11T12:59:14.162840Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.148763Z","title":"a henb \\","venue":null,"work_id":"03cbe7b7-59c0-4666-a927-014d925e92a6","year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.567702Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:1de3b21e2c765e47a00f5d1c5bddc2bd08120fdd49ee443526b6b81f6fc89b8d","observation_id":"734a99d1-c00d-4e22-bb81-bc4b44c08ce6","resolution":{"observed_at":"2026-08-11T12:59:14.152491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.139553Z","title":null,"venue":null,"work_id":"2d75eee1-2330-48b4-9fa7-5eaeafac5e96","year":2023},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.571394Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:eaf5a5547b34f2c470c2e232a836f81e50187630bb7fd3a18292c24e5bd5e6f1","observation_id":"8c2bac30-73e1-4b26-ade2-55599016bd2c","resolution":{"observed_at":"2026-08-11T12:59:14.142658Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.130576Z","title":null,"venue":null,"work_id":"b51b3a6d-029b-4562-90e9-dd687a01a4ed","year":2022},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.574875Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:6fd9e678f7fd9667eb714c2af75b4a7d6d665cdc079bf8ed2ba7894236ddb9d6","observation_id":"fbf14413-b92c-4036-8a00-eea48d779e6c","resolution":{"observed_at":"2026-08-11T12:59:14.133786Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.120112Z","title":null,"venue":null,"work_id":"1e3c2a7d-ac79-494b-9b74-8fa08b0a06f2","year":2022},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.578528Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:7ab08c68a3132cfced8119e89f4bd3d2d5238669a62fb408985abae932394844","observation_id":"cc506e34-4d86-4fb2-8cff-ccc753cc53c2","resolution":{"observed_at":"2026-08-11T12:59:14.123767Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.581830Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.581830Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:eb54d61573fade210030409b19e841a3f02a11917f47468bc7ff46961b73a302","observation_id":"dc9973a5-01a0-473d-929b-c3fb8944deda","resolution":{"observed_at":"2026-08-11T12:59:13.581830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.02778","last_updated":"2022-09-06T19:02:08Z","snapshot_observed_at":"2026-08-16T20:20:04.765331Z","submitted_at":"2022-09-06T19:02:08Z","title":"Multi-skill Mobile Manipulation for Object Rearrangement","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.02778","snapshot_observed_at":"2026-08-11T12:59:13.585296Z","title":"S.; Su, H.; and Malik, J","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.585296Z"},"links":{"cited_paper":"/paper/2209.02778","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:1401764b172dc70e773ac7a34dfd6db09e40a0a7f53d43680718f44819ec4149","observation_id":"05e6436a-c588-4a44-a6aa-0bb5dbcf90c6","resolution":{"observed_at":"2026-08-11T12:59:13.585296Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.104663Z","title":null,"venue":null,"work_id":"86389fb0-e95d-4770-98a2-9163021b655b","year":2023},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.589563Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:c1eb0efe24b590c2880232ec96ed2b6bd33c472f5024e667ec4145067fb8aa48","observation_id":"672bcd59-2abf-45f7-a2fc-c2be9666a460","resolution":{"observed_at":"2026-08-11T12:59:14.108117Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.592853Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.592853Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:f242e6b5b42076b82553a5b34afadf92565b6294cd7467291ac88829e106eebe","observation_id":"d8acde60-d2f3-4992-9d9f-60b7d63d07df","resolution":{"observed_at":"2026-08-11T12:59:13.592853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.01603","last_updated":"2020-03-17T17:10:58Z","snapshot_observed_at":"2026-08-15T17:22:37.525122Z","submitted_at":"2019-12-03T18:57:16Z","title":"Dream to Control: Learning Behaviors by Latent Imagination","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.01603","snapshot_observed_at":"2026-08-11T12:59:13.595995Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.595995Z"},"links":{"cited_paper":"/paper/1912.01603","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:9af0dda64f1a2aa78c4d37d54c2a82a6cbb7beac61d25321a3e84fbe2a922ca8","observation_id":"7f176129-b215-4958-bb00-a55556b84cf1","resolution":{"observed_at":"2026-08-11T12:59:13.595995Z","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":"2026-08-11T12:59:13.599488Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.599488Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:c609eac5e5546b1b9eabea2ff67cfdcf458e2b74f03c859ff1501e4387bdd34b","observation_id":"06846b4e-61d9-4624-88f4-bbff923bd784","resolution":{"observed_at":"2026-08-11T12:59:13.599488Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.082379Z","title":null,"venue":null,"work_id":"c5cc0ca6-8186-499d-9439-0266d2c3a378","year":2019},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.602263Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:b21e69c3f8def93c8f58c22dd324ced4fca0476be7f506cfa930f4088cbea5b7","observation_id":"10efb08c-e0b4-44a8-a2a1-da525e2b97c6","resolution":{"observed_at":"2026-08-11T12:59:14.085931Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02193","last_updated":"2022-02-12T20:01:53Z","snapshot_observed_at":"2026-08-17T02:57:21.304714Z","submitted_at":"2020-10-05T17:52:14Z","title":"Mastering Atari with Discrete World Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02193","snapshot_observed_at":"2026-08-11T12:59:13.604994Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.604994Z"},"links":{"cited_paper":"/paper/2010.02193","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:abb613e6cdb589b629e32eb2e5ddd12e8d427793173b0ad6bf820ca8e95301d3","observation_id":"1ef51db8-183e-4fc4-b89f-8cb4d0e77df4","resolution":{"observed_at":"2026-08-11T12:59:13.604994Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.04955","last_updated":"2022-07-19T18:14:36Z","snapshot_observed_at":"2026-08-16T17:15:47.150759Z","submitted_at":"2022-03-09T18:58:28Z","title":"Temporal Difference Learning for Model Predictive Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.04955","snapshot_observed_at":"2026-08-11T12:59:13.608629Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.608629Z"},"links":{"cited_paper":"/paper/2203.04955","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:9ff663e685b25eb339fafe5468532af8a5ab4ab50b35f8618a0f2fada2499b28","observation_id":"849bc0a6-5669-4966-b30f-cba66282de56","resolution":{"observed_at":"2026-08-11T12:59:13.608629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.11217","last_updated":"2023-06-20T00:54:20Z","snapshot_observed_at":"2026-08-16T15:22:42.977905Z","submitted_at":"2023-06-20T00:54:20Z","title":"Autonomous Driving with Deep Reinforcement Learning in CARLA Simulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.11217","snapshot_observed_at":"2026-08-11T12:59:13.612207Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.612207Z"},"links":{"cited_paper":"/paper/2306.11217","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:d6ed766bebc76717647298de39db60d5aba4619215512dcca550648159081888","observation_id":"58c68a5f-8543-4199-8787-8b74e8a63477","resolution":{"observed_at":"2026-08-11T12:59:13.612207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.073302Z","title":null,"venue":null,"work_id":"c9e2651e-b525-4b3b-9062-8389a8218846","year":2018},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.616117Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:cf205d606aa720bbafae69d874b73bc65bde1fb3293ac564365ed25bc9c89af1","observation_id":"e989014f-07b0-46d5-b950-3b7d51428ab5","resolution":{"observed_at":"2026-08-11T12:59:14.076497Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.063968Z","title":null,"venue":null,"work_id":"eec584e9-37cb-4804-b262-c30c8c17295e","year":2023},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.619557Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:0e4601a42741b677bd680c591a6cda501b7a790750550c12d4c5429aaf15fe8a","observation_id":"982d36cf-855f-4790-8c0e-e194d8bf6b88","resolution":{"observed_at":"2026-08-11T12:59:14.067283Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-08-15T20:26:32.102285Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-11T12:59:13.622908Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.622908Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:f62429bc9783f64f19015a57df1e16f79243787e6791c1fcd075c55ae5c77355","observation_id":"8b9b2fca-4ebe-413c-861d-b4af0ecdca37","resolution":{"observed_at":"2026-08-11T12:59:13.622908Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.13649","last_updated":"2021-03-07T16:37:37Z","snapshot_observed_at":"2026-08-16T04:03:26.547476Z","submitted_at":"2020-04-28T16:48:16Z","title":"Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.13649","snapshot_observed_at":"2026-08-11T12:59:13.626353Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.626353Z"},"links":{"cited_paper":"/paper/2004.13649","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:922996261b06aa17c66b75a0c9f6283f6038814bebe63c8ff291cf45a7c2fcf9","observation_id":"d52af63a-5acd-4a6e-bb27-a0f29ef2e198","resolution":{"observed_at":"2026-08-11T12:59:13.626353Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.052945Z","title":"D.; Gupta, A.; Ionescu, C.; Borgeaud, S.; Reynolds, M.; Zisserman, A.; and Mnih, V","venue":null,"work_id":"6bac51c4-1777-4505-b154-74e8beebd734","year":2019},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.629939Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:2feca42d1ae592392ce90392b9d4d16f2d4aee46378d5d66924729daa3f51869","observation_id":"72a0c890-f99f-4b03-93d3-485df68ffd1d","resolution":{"observed_at":"2026-08-11T12:59:14.056843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.04034","last_updated":"2021-07-08T17:59:59Z","snapshot_observed_at":"2026-08-18T15:06:14.253218Z","submitted_at":"2021-07-08T17:59:59Z","title":"RMA: Rapid Motor Adaptation for Legged Robots","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.04034","snapshot_observed_at":"2026-08-11T12:59:13.633183Z","title":"???? Rma: Rapid motor adaptation for legged robots","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.633183Z"},"links":{"cited_paper":"/paper/2107.04034","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:66d1bf205c51c2fe4bfb6d4cfd4795d1b9956f2f31d09e968b57cfc42815f4cf","observation_id":"2e95c936-1324-47f7-926d-9375addb7283","resolution":{"observed_at":"2026-08-11T12:59:13.633183Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.042745Z","title":null,"venue":null,"work_id":"2f3e05a3-ff2e-40ee-ba8c-b135d4398c2d","year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.636603Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:1aac268b0f6c90212883d0b119c2fd514a87e80a540c21a3185000b73631e291","observation_id":"0b3e8d53-25f1-4cf3-891f-897a9c1e7cbf","resolution":{"observed_at":"2026-08-11T12:59:14.046127Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.032659Z","title":null,"venue":null,"work_id":"6eedf9df-2aa1-4d78-a5d3-8ddc1e1bf7a7","year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.639815Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:2c1e8d21dbbce014afcb936b35c765f8d422a4e3154c4944ae6dd9b2116d612e","observation_id":"eb256622-01b2-49d1-a714-78c2e4ca7608","resolution":{"observed_at":"2026-08-11T12:59:14.036135Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.021967Z","title":null,"venue":null,"work_id":"ff61ae66-08c2-4243-a3a1-5af921f1a474","year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.643442Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:7a9f946b938628b0d8001a1373a291569c96672cf7a17d0d07b1f40d2403bd58","observation_id":"6cee6915-9267-4213-996f-93a766b7859d","resolution":{"observed_at":"2026-08-11T12:59:14.025636Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1509.02971","last_updated":"2019-07-05T10:47:27Z","snapshot_observed_at":"2026-08-16T22:06:26.835611Z","submitted_at":"2015-09-09T23:01:36Z","title":"Continuous control with deep reinforcement learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1509.02971","snapshot_observed_at":"2026-08-11T12:59:13.646715Z","title":"P.; Hunt, J","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.646715Z"},"links":{"cited_paper":"/paper/1509.02971","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:ecb45dbf1f63b4d6673d5c8093e728b0022475a3d6580c4d41e2a4aabfb0aaab","observation_id":"6c41da68-aac2-4a5c-82d8-df4e515c640a","resolution":{"observed_at":"2026-08-11T12:59:13.646715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.011436Z","title":null,"venue":null,"work_id":"aebb4864-9916-4dd1-ae6b-4b007f071fba","year":2021},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.650274Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:e67cb6ea969e34d458b44fac47f36e533bd2449b1b1127836717f8b4ce38e0b8","observation_id":"a9d3e045-250b-4f18-b993-06ac8ddb7c01","resolution":{"observed_at":"2026-08-11T12:59:14.014654Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.15344","last_updated":"2021-10-28T17:53:06Z","snapshot_observed_at":"2026-08-18T17:43:36.183430Z","submitted_at":"2021-10-28T17:53:06Z","title":"Learning to Jump from Pixels","version":1},"cited_work":{"arxiv_id":"2110.15344","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.15344","snapshot_observed_at":"2026-08-11T12:59:13.798220Z","title":"Learning to Jump from Pixels","venue":"cs.RO","work_id":"c1a23911-9149-456d-9c19-ab2d6a773018","year":2021},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.653611Z"},"links":{"cited_paper":"/paper/2110.15344","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:f435c4bcdf617c5976c6461b505e72f0e83d0441e88dbae30a8782062a2db164","observation_id":"5b2671db-9fd3-4f85-ab19-4f5e5a24a75a","resolution":{"observed_at":"2026-08-11T12:59:13.803315Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:14.000447Z","title":null,"venue":null,"work_id":"28cd20b4-9729-46d1-bb10-b622c2c61700","year":2022},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.657171Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:ad78b2ab4f721029e8b71214c73243f206eafe4b5968515e966ae80fd00f3144","observation_id":"bbfd5a31-78c9-40eb-865e-315cc09d313d","resolution":{"observed_at":"2026-08-11T12:59:14.004562Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.660406Z","title":"A.; Veness, J.; Bellemare, M","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.660406Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:36d24606764226e1078aa752650a2b9e3b79d083c88eedfbcc5d5224c980d81d","observation_id":"594e9fa2-e290-4c6c-a7a6-5049d6a2a87e","resolution":{"observed_at":"2026-08-11T12:59:13.660406Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.14483","last_updated":"2021-11-04T12:11:21Z","snapshot_observed_at":"2026-08-16T18:06:24.201768Z","submitted_at":"2021-07-30T08:20:22Z","title":"ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.14483","snapshot_observed_at":"2026-08-11T12:59:13.663610Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.663610Z"},"links":{"cited_paper":"/paper/2107.14483","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:2cbe5413296e66b1e4bd5464065e418ff27ac13816ec94e3dd751c1223c8e64c","observation_id":"65479485-a6d4-4c2c-b80c-874322468c70","resolution":{"observed_at":"2026-08-11T12:59:13.663610Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.983403Z","title":"V.; Pong, V.; Dalal, M.; Bahl, S.; Lin, S.; and Levine, S","venue":null,"work_id":"da442dc7-399b-4409-8c4f-7bcf340ec3b1","year":2018},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.666948Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:6e960b8e13abfdce7a0183e40956f6423f538992f92df360c3d1e064bf04b5a7","observation_id":"ef5cbcab-0731-4e44-8993-304f017229cc","resolution":{"observed_at":"2026-08-11T12:59:13.987811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.972901Z","title":null,"venue":null,"work_id":"d50b712c-39e5-47ec-b248-eb0fc91b7170","year":2022},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.670473Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:a0ebfa93e962a213768c6a9403aaa8913d432966c6214803786f95ce46566543","observation_id":"ac156282-57ad-4bee-a771-e61fa3f58a9f","resolution":{"observed_at":"2026-08-11T12:59:13.976217Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.06542","last_updated":"2017-10-18T01:10:37Z","snapshot_observed_at":"2026-08-14T20:22:42.955584Z","submitted_at":"2017-10-18T01:10:37Z","title":"Asymmetric Actor Critic for Image-Based Robot Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.06542","snapshot_observed_at":"2026-08-11T12:59:13.673928Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.673928Z"},"links":{"cited_paper":"/paper/1710.06542","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:20dd695b9da07f4b618ea5a6559ce7f3faa7a4b2a71a7fa9571da8bcc14722b4","observation_id":"c302df5c-70a2-4404-bc8b-1fd279ef95c8","resolution":{"observed_at":"2026-08-11T12:59:13.673928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1709.10087","last_updated":"2018-06-26T13:31:37Z","snapshot_observed_at":"2026-08-15T17:49:11.636243Z","submitted_at":"2017-09-28T17:51:13Z","title":"Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.10087","snapshot_observed_at":"2026-08-11T12:59:13.677490Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.677490Z"},"links":{"cited_paper":"/paper/1709.10087","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:1b47f3e42d90f9f860bf195e342a1fd89fb0c8368e5fc0ba98611428e31b44ff","observation_id":"69691322-7a47-41f2-a269-591103966300","resolution":{"observed_at":"2026-08-11T12:59:13.677490Z","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":"2026-08-11T12:59:13.680485Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.680485Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:adb635ef9ed296d390ceaa030a60487e76da63400a78116aa705792e32ea239d","observation_id":"ab4b50cf-079b-49b0-8c48-bf48eff36482","resolution":{"observed_at":"2026-08-11T12:59:13.680485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03380","last_updated":"2021-11-11T19:06:52Z","snapshot_observed_at":"2026-08-16T18:11:38.245504Z","submitted_at":"2021-07-07T17:59:07Z","title":"RRL: Resnet as representation for Reinforcement Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.03380","snapshot_observed_at":"2026-08-11T12:59:13.683257Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.683257Z"},"links":{"cited_paper":"/paper/2107.03380","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:e31eb14e94368dac0a85455f4edb71d6a40aa774adea955c16ea71af1b25e03b","observation_id":"d448f652-4a72-4bb9-a54a-785b4d658368","resolution":{"observed_at":"2026-08-11T12:59:13.683257Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.956677Z","title":null,"venue":null,"work_id":"33a35793-74b5-4246-a64e-44df087fb17b","year":2021},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.686368Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:c4faef5713a89b386c8534f8f3b80f6d24303eba8e8ab5905297e1ad35289d22","observation_id":"e381edea-cec3-4c0c-a915-079ac8594b3c","resolution":{"observed_at":"2026-08-11T12:59:13.960378Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.945913Z","title":null,"venue":null,"work_id":"b9a2ef5b-b62c-4310-978b-f53ada284695","year":2013},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.689357Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:d03ff94a28376023626bc2bcd91701e4019696eab78baab2e776345f9fe3dea9","observation_id":"490953d4-a3ea-4484-997c-3c684fa80ea5","resolution":{"observed_at":"2026-08-11T12:59:13.949447Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1801.00690","last_updated":"2018-01-02T15:48:14Z","snapshot_observed_at":"2026-08-01T20:24:08.300098Z","submitted_at":"2018-01-02T15:48:14Z","title":"DeepMind Control Suite","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.00690","snapshot_observed_at":"2026-08-11T12:59:13.692376Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.692376Z"},"links":{"cited_paper":"/paper/1801.00690","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:5f25f7177d18e0ff76608c37ef87e8058b2a4b82be6a81198bb0c9b81728cf76","observation_id":"60759d72-b6ed-4eb5-805d-bc931de3135f","resolution":{"observed_at":"2026-08-11T12:59:13.692376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.935440Z","title":null,"venue":null,"work_id":"21432d38-66ba-4900-a5cd-5ea674be85a4","year":2023},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.695770Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:9eaae7882840ab3d7f0770ff954138c57a2ff7ffc4336a8e1ea1a5813927ee2b","observation_id":"248f6876-a531-47d6-89dd-0b25a4f320f6","resolution":{"observed_at":"2026-08-11T12:59:13.939035Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.924500Z","title":null,"venue":null,"work_id":"944e92c4-8dd5-41bb-8433-dbfc3c667a82","year":2020},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.699112Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:ea2d3b4755684a5a009b16540d4a63f74261bdc0fa84e4dee56e11fa89194405","observation_id":"052fd75f-ef3b-4fe4-bfe9-2a2e90587c2d","resolution":{"observed_at":"2026-08-11T12:59:13.928401Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.914038Z","title":null,"venue":null,"work_id":"e3fdb2e1-14f7-4f45-839b-cfcd5d94026c","year":2024},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.702322Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:09ab5c171745147ca8c4001d5d42d58a380c3e08121c714357e4cdc27d74fcb8","observation_id":"ffb4b9d2-5121-484b-8291-ad632fb3537f","resolution":{"observed_at":"2026-08-11T12:59:13.917695Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T12:59:13.903497Z","title":"a henb \\","venue":null,"work_id":"3dd81419-7c51-4f69-b8da-2c09bb3e705c","year":2019},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.705667Z"},"links":{"citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:2673171e2a64e3452557a8c0961f91de317823bc0c80ac98186725a4d7b23c47","observation_id":"8acf54f0-6c1e-42ca-94f2-c637690dc50e","resolution":{"observed_at":"2026-08-11T12:59:13.907101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05665","last_updated":"2023-09-12T03:01:55Z","snapshot_observed_at":"2026-08-16T15:01:38.241828Z","submitted_at":"2023-09-11T17:59:17Z","title":"Robot Parkour Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05665","snapshot_observed_at":"2026-08-11T12:59:13.709099Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-11T12:59:13.709099Z"},"links":{"cited_paper":"/paper/2309.05665","citing_paper":"/paper/2412.13662"},"observation_digest":"sha256:76408f190303364ae44acc17c0b55e5b21487e50eae62a535902cc17649199f2","observation_id":"090e7dbb-ab93-4dc6-985c-341a52ea2fe1","resolution":{"observed_at":"2026-08-11T12:59:13.709099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.13662","last_updated":"2024-12-18T09:39:12Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-14T16:00:45.899681Z","submitted_at":"2024-12-18T09:39:12Z","title":"When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement Learning?"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":43,"verified_exact":0,"verified_fuzzy":4},"total_outbound_references":48},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2412.13662."}