{"as_of":"2026-08-20T20:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3b433a856bb914b965cf422496164d7dfb92b24c06ec95abda29635c86b3b76b","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T23:09:55.652593Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.05838/citation-record","integrity":"/paper/2508.05838/integrity","json":"/paper/2508.05838/citation-record.json","paper":"/paper/2508.05838"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T23:09:55.921814Z","title":"Mask r-cnn,","venue":null,"work_id":"240afb8f-e0b2-40e4-b6ee-c3dfbf06cbad","year":2017},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.569647Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:c36da431055aeb1d8d2bfaa511b1aacd2dd12c66fb5ed06d085af2c4d6b21430","observation_id":"61fb4cb9-880b-4348-b47f-dea3a0d23381","resolution":{"observed_at":"2026-08-05T23:09:55.924783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.912404Z","title":"Yolo9000: Better, faster, stronger,","venue":null,"work_id":"42499ec8-3b28-4d7d-921a-6ab61025f1d0","year":2017},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.572914Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:9071c8ae26e93cdc93cb24800f4411eaf3e5df7777cbb0fd9879cacfe7c300e5","observation_id":"bc9e1c57-cc85-413d-bdbe-2afa957f23ef","resolution":{"observed_at":"2026-08-05T23:09:55.915435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.576703Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.576703Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:1034da4492bb5dc311db5e195d0eccc96533ceb042f0892d6d37927702624fab","observation_id":"5a0bb935-5bad-4995-a8f7-c9a2e10d0728","resolution":{"observed_at":"2026-08-05T23:09:55.576703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-08-20T07:04:06.309989Z","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":"2026-08-05T23:09:55.579670Z","title":"Proxi- mal policy optimization algorithms,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.579670Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:c387ae686266761df3669300b4441fa59088943adf534fc80676b70be501a17d","observation_id":"4db697e7-d429-46dc-ab4e-d788e2b36237","resolution":{"observed_at":"2026-08-05T23:09:55.579670Z","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":"2026-08-05T23:09:55.895821Z","title":"Target-driven visual navigation in indoor scenes using deep reinforcement learning,","venue":null,"work_id":"5ebbf728-86fa-44a9-ad0b-cb517b388343","year":2017},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.583144Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:bbe2970fa2229aeb2ec220ca3e9c32a94571d4140372eff0e7bf38c11227ee93","observation_id":"f0be7099-df7a-4c60-aef9-750e71b2f68a","resolution":{"observed_at":"2026-08-05T23:09:55.899227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.885946Z","title":"Cognitive mapping and planning for visual navigation,","venue":null,"work_id":"ff70af04-8c7e-43cb-9a9a-a975027f82a6","year":2017},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.586880Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:94cb94a64fd23bfb2d4ab587b91168764dbeccb09ee05c1a16e38653cbb07814","observation_id":"98f470db-67ca-4ca1-80af-7b227764bca3","resolution":{"observed_at":"2026-08-05T23:09:55.889658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.875877Z","title":"Qt-opt: Scalable deep reinforcement learning for vision-based robotic manipulation,","venue":null,"work_id":"a16fa245-86bb-4d90-9a6f-f124a22f0791","year":2018},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.590235Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:8e62d78f857e961b2ff8e53cfb0be803bb44c8ac0b8611a7fe5ade646b6f4e02","observation_id":"3802a023-6a20-4a6a-beec-996ae525829d","resolution":{"observed_at":"2026-08-05T23:09:55.879512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.865214Z","title":"Learning dexterous in-hand manipulation,","venue":null,"work_id":"5e714c90-9d46-4de7-9253-18ebf1d7991c","year":2020},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.593235Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:367423c83c06cd56a16f75e4359dd8491a6951b3f1f579259f1a9ff06e23ecc7","observation_id":"904abb9a-a45f-4c34-9073-0a7d701a6189","resolution":{"observed_at":"2026-08-05T23:09:55.868914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.855321Z","title":"Concept2robot: Learning manipulation concepts from instructions and human demon- strations,","venue":null,"work_id":"2c2cb98d-21f2-4194-abb9-4aeee344827f","year":2020},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.596334Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:29ae3ec0a791526cb00a8c5cfa08b5c4f1956076e122530fef946e0e1d9662cb","observation_id":"a20d250f-7bb4-484d-b64a-f136155ce21e","resolution":{"observed_at":"2026-08-05T23:09:55.859289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.846513Z","title":"Robots that use language,","venue":null,"work_id":"884d72f7-0788-4890-b551-a751b546781d","year":2020},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.599010Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:e5ddafcc6c8a58bd005e1e4c227916e1c679571eb5ecf47155242a4a1c93db65","observation_id":"3c791e4d-e321-4a72-9776-e3b072a9cd4d","resolution":{"observed_at":"2026-08-05T23:09:55.849482Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.836861Z","title":"YOLOv5 by Ultralytics,","venue":null,"work_id":"7a0f899e-92b1-436f-bdc3-7bafe42cf767","year":2020},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.602147Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:f159a02404a891da85f542aa48239be8348340ae6877bfb7215dc06d5878f4be","observation_id":"18a68691-f489-46ef-8be8-abdec5ac50de","resolution":{"observed_at":"2026-08-05T23:09:55.840313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.02643","last_updated":"2023-04-05T17:59:46Z","snapshot_observed_at":"2026-08-08T05:14:59.435033Z","submitted_at":"2023-04-05T17:59:46Z","title":"Segment Anything","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.02643","snapshot_observed_at":"2026-08-05T23:09:55.605004Z","title":"Segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.605004Z"},"links":{"cited_paper":"/paper/2304.02643","citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:be978a8f816fd5b1673b72d9148204d35cde97a8688e9bb103c5d4cbc80f3eb4","observation_id":"a49ed6bb-5387-46d6-ac00-8309e67a4798","resolution":{"observed_at":"2026-08-05T23:09:55.605004Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.05474","last_updated":"2022-08-26T17:12:17Z","snapshot_observed_at":"2026-08-14T05:42:22.751765Z","submitted_at":"2017-12-14T23:17:24Z","title":"AI2-THOR: An Interactive 3D Environment for Visual AI","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.05474","snapshot_observed_at":"2026-08-05T23:09:55.608595Z","title":"Ai2-thor: An interactive 3d environment for visual ai,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.608595Z"},"links":{"cited_paper":"/paper/1712.05474","citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:a892990a660ecb3d4949b39c5abdfb48dcaec028dfdb06a8e2e4384c391b6d4d","observation_id":"78d2c553-7450-48de-9bfc-cc78f2d38056","resolution":{"observed_at":"2026-08-05T23:09:55.608595Z","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":"2026-08-05T23:09:55.611579Z","title":"Reinforcement learning in robotics: A survey,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.611579Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:966f20a4adb0c874c74afa02b735e853141830f8a60f6f9f02107a3fd63e3f91","observation_id":"0185f790-57db-4b72-9ca5-04196379eb58","resolution":{"observed_at":"2026-08-05T23:09:55.611579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-05T23:09:55.614147Z","title":"Continuous control with deep reinforcement learning,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.614147Z"},"links":{"cited_paper":"/paper/1509.02971","citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:6c4622aaa22f5edee4fc3b0ff48989100e260442160d37c0169850f066cbb216","observation_id":"01dd3e8e-f208-4f10-aeb0-0f6cee61339e","resolution":{"observed_at":"2026-08-05T23:09:55.614147Z","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":"2026-08-05T23:09:55.617361Z","title":"End-to-end training of deep visuomotor policies,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.617361Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:534e079b200574340b79cd54fc87d7fe03f8bd65a85aea77ddd44c7e39d9e756","observation_id":"052d3dbe-d179-4ad8-9a0e-e885d127def9","resolution":{"observed_at":"2026-08-05T23:09:55.617361Z","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":"2026-08-05T23:09:55.817849Z","title":"Trust region policy optimization,","venue":null,"work_id":"90f7217e-80c0-469f-8842-9fa1d8af2c98","year":2015},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.619964Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:a8314cecbc71fdb111d59cee9c161d566a652b96b0b84d0651d1f8d9e27617db","observation_id":"22f7918e-bd78-4ae3-9aed-c1dd6fc49f22","resolution":{"observed_at":"2026-08-05T23:09:55.820384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.02286","last_updated":"2017-07-10T18:52:12Z","snapshot_observed_at":"2026-08-14T20:48:59.676482Z","submitted_at":"2017-07-07T17:56:57Z","title":"Emergence of Locomotion Behaviours in Rich Environments","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.02286","snapshot_observed_at":"2026-08-05T23:09:55.622714Z","title":"Emergence of locomotion behaviours in rich environ- ments,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.622714Z"},"links":{"cited_paper":"/paper/1707.02286","citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:794e865538e1836229ddba460481f693ae9680450fbd22961b8ebd46ecca47f5","observation_id":"ebe9380b-fbc7-4fa1-b190-284278198cdc","resolution":{"observed_at":"2026-08-05T23:09:55.622714Z","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":"2026-08-05T23:09:55.808569Z","title":"Sim-to-real transfer in deep reinforcement learning for robotics: A survey,","venue":null,"work_id":"da0d0bd1-d87b-45ae-a7f4-f272c02845f8","year":2020},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.626230Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:131db8f15ebd922565f239196301df4a0f90402ecf3324c0187d3a48dede3531","observation_id":"61be4019-8a45-4ffd-b508-efae4915f10f","resolution":{"observed_at":"2026-08-05T23:09:55.811784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.800656Z","title":"Deep reinforcement learning for robotics: A survey,","venue":null,"work_id":"455dcf6c-5813-4bea-a0b0-7997b2de4bab","year":2018},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.629100Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:75025af417ca622784a6be77977bf57cd899dc1e00305a0bf41e78db4263eba4","observation_id":"614da88d-65c2-40f2-9907-03d9670b1ee7","resolution":{"observed_at":"2026-08-05T23:09:55.803471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.791368Z","title":"Human-level control through deep reinforcement learning,","venue":null,"work_id":"e9bd2d95-8fd6-416c-aa7a-1071d82481b8","year":2015},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.632711Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:136f4ef9356f5c898f576b5aaf64c43c69328be1831d0132592f09f43b933a6f","observation_id":"0224ef50-1226-496a-8e8e-432f864390e0","resolution":{"observed_at":"2026-08-05T23:09:55.794264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.780374Z","title":"Visual representations for semantic target driven navigation,","venue":null,"work_id":"164e8983-b4e2-4a68-b40a-98a8c595d8c6","year":2019},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.635733Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:a6f9d5265e97d8dfd07f355e89dd30b6cdf74ff94fec24cfd1cc7dd88d689f0f","observation_id":"6709528f-22d5-4b31-b6e5-91ff93367e7a","resolution":{"observed_at":"2026-08-05T23:09:55.784635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.768965Z","title":"Object goal navigation using goal-oriented semantic exploration,","venue":null,"work_id":"9732b331-509b-44cc-b1a6-e01c52f0fb9a","year":2020},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.638612Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:f52084cd2eaad4153b0bf81114564046ab7519bef75777f305c8f592b84d241f","observation_id":"446fe3cf-4e90-4693-ad68-63ca4ece1a27","resolution":{"observed_at":"2026-08-05T23:09:55.773439Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.759515Z","title":"Reinforced cross-modal matching and self-supervised imitation learning for vision-language navigation,","venue":null,"work_id":"6edbbb10-7e39-4495-aab1-cc67a99f51f8","year":2019},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.641580Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:60ccc5a19b04f47e9760c1524e27576785e1ed509016c67c3d5a0496950554d0","observation_id":"48f80a92-3b5b-4a6f-a956-0efb248de95c","resolution":{"observed_at":"2026-08-05T23:09:55.762485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.750760Z","title":"Faster r-cnn: Towards real-time object detection with region proposal networks,","venue":null,"work_id":"12a1eae4-74bb-45fc-993e-9c1ffa92f260","year":2015},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.644552Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:b43c03fd6d4d6ad811b3f24ed81a46fab2d013fa9f6d96702fa412631df9bf8b","observation_id":"fe3d4789-8ed5-4517-a1d7-e24501c1217d","resolution":{"observed_at":"2026-08-05T23:09:55.754013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.741641Z","title":"Habitat: A platform for embodied ai research,","venue":null,"work_id":"907f28e9-52d7-42b3-a3db-49c787a1b2cf","year":2019},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.647506Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:edf9d114015dab85bb162c37f49fde725ee91cf9af383661939f296846be813b","observation_id":"9335984e-f5f0-4dc4-b568-64e33d9bf939","resolution":{"observed_at":"2026-08-05T23:09:55.744752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.732596Z","title":"Gibson env: Real-world perception for embodied agents,","venue":null,"work_id":"c5de87d0-0b82-4c7f-a264-f0b0d22e912f","year":2018},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.649967Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:1a8c576f9cb0d11ab105cfc8ed2e58c105ce095ab5dd94ff10efd76fbe464981","observation_id":"682675f2-eb34-4f70-8043-fec33ea4cb82","resolution":{"observed_at":"2026-08-05T23:09:55.735795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-05T23:09:55.721876Z","title":"Pytorch: An imperative style, high-performance deep learning library,","venue":null,"work_id":"48851f6a-6c19-48dd-90ca-4f035f13d96a","year":2019},"citing_paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T23:09:55.652593Z"},"links":{"citing_paper":"/paper/2508.05838"},"observation_digest":"sha256:d79bfb20f426c9354e8a90c8750249528b8afb41d68432e14ab0423241cea2cc","observation_id":"40f6f483-63b4-4e6d-979e-9650a39f6fea","resolution":{"observed_at":"2026-08-05T23:09:55.726371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.05838","last_updated":"2025-08-07T20:29:01Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-14T12:25:32.591021Z","submitted_at":"2025-08-07T20:29:01Z","title":"Integrating Vision Foundation Models with Reinforcement Learning for Enhanced Object Interaction"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":0,"verified_fuzzy":20},"total_outbound_references":28},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2508.05838."}