{"as_of":"2026-08-06T17:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:214833716cab3fd9a0ba15bef84c1522058612f6c488248cb8a354c69e4efeba","coverage":[{"denominator":83,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":83,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-11T00:48:43.992238Z","state":"measured"},{"denominator":87,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":87,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T05:01:06.189476Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-03T20:08:56.590301Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"cited_work":{"arxiv_id":"2604.24661","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.24661","snapshot_observed_at":"2026-07-03T20:08:56.590301Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","venue":"cs.RO","work_id":"9378de18-6e45-4952-ab4a-71f8f59cffcf","year":2026},"citing_paper":{"arxiv_id":"2605.29471","last_updated":"2026-08-01T06:57:33Z","snapshot_observed_at":"2026-08-06T16:12:38.106480Z","submitted_at":"2026-05-28T07:03:51Z","title":"V2VCrafter: Consistent Street-View Image Generation Across Vehicles","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-29T08:54:44.386180Z"},"links":{"cited_paper":"/paper/2604.24661","citing_paper":"/paper/2605.29471"},"observation_digest":"sha256:1770e7e95059018f36c91e2b60ad530b6f170939126ad2177590809569ce9f40","observation_id":"68f8ec7d-40ec-4178-905e-df5eca684075","resolution":{"observed_at":"2026-06-29T09:03:16.170109Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.24661","snapshot_observed_at":"2026-08-04T05:01:06.189476Z","title":"Agent-centric visual reinforcement learning under dynamic perturbations.arXiv preprint arXiv:2604.24661, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2605.29471","last_updated":"2026-08-01T06:57:33Z","snapshot_observed_at":"2026-08-06T16:12:38.106480Z","submitted_at":"2026-05-28T07:03:51Z","title":"V2VCrafter: Consistent Street-View Image Generation Across Vehicles","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T05:01:06.189476Z"},"links":{"cited_paper":"/paper/2604.24661","citing_paper":"/paper/2605.29471"},"observation_digest":"sha256:7af3ca92f53536d6dd0f638f34a9d54c53cfc489a903595bfc320f80b14b6e26","observation_id":"1612deaa-981d-4b15-a364-3c0648e3a10a","resolution":{"observed_at":"2026-08-04T05:01:06.189476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"cited_work":{"arxiv_id":"2604.24661","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.24661","snapshot_observed_at":"2026-07-03T20:08:56.590301Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","venue":"cs.RO","work_id":"9378de18-6e45-4952-ab4a-71f8f59cffcf","year":2026},"citing_paper":{"arxiv_id":"2605.29997","last_updated":"2026-05-28T14:27:30Z","snapshot_observed_at":"2026-07-06T23:39:20.085961Z","submitted_at":"2026-05-28T14:27:30Z","title":"FRUC: Feedforward Dynamic Scene Reconstruction from Uncalibrated Collaborative Driving Views","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-29T08:19:06.917721Z"},"links":{"cited_paper":"/paper/2604.24661","citing_paper":"/paper/2605.29997"},"observation_digest":"sha256:d532756cb4d7652da139a5f16486929035e1be3a964b2609c75e1ae7bf48a4ee","observation_id":"1a566166-aff7-4eee-b9f6-7da096beee1b","resolution":{"observed_at":"2026-06-29T08:23:15.221048Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"cited_work":{"arxiv_id":"2604.24661","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.24661","snapshot_observed_at":"2026-07-03T20:08:56.590301Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","venue":"cs.RO","work_id":"9378de18-6e45-4952-ab4a-71f8f59cffcf","year":2026},"citing_paper":{"arxiv_id":"2606.17557","last_updated":"2026-06-16T06:01:36Z","snapshot_observed_at":"2026-08-03T23:48:44.120434Z","submitted_at":"2026-06-16T06:01:36Z","title":"Universal Image Restoration via Internalized Chain-of-Thought Reasoning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T01:34:34.269899Z"},"links":{"cited_paper":"/paper/2604.24661","citing_paper":"/paper/2606.17557"},"observation_digest":"sha256:d18f50e8f87b39829002c4daecaf0bff441cf616407c299c335678bec6c3b71c","observation_id":"866abc80-79d5-42ea-b297-555ac424c9ec","resolution":{"observed_at":"2026-07-03T20:08:56.592588Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2604.24661/citation-record","integrity":"/paper/2604.24661/integrity","json":"/paper/2604.24661/citation-record.json","paper":"/paper/2604.24661"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Look where you look! Saliency-guided q-networks for generalization in visual reinforcement learning.Advances in neural information processing systems, 35:30693–30706","venue":null,"work_id":"e2adef88-dcd7-4b9f-8f55-2f31cb535c8d","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:9838cc25fcafe10fd13b5693fa84e563ef3716210e06ee94b6f014ccd424d62b","observation_id":"ecebc2e7-6674-4883-8fad-fc2c6a30ebe5","resolution":{"observed_at":"2026-05-16T01:17:04.134917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Parameter-free online test-time adaptation","venue":null,"work_id":"0d5c5f32-9a73-4c9a-a5e4-b04723f9ed02","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:f4b5b171d7417b6cfc1881ec7fccac59aea1953bfaeea0b24de423a38ff0a467","observation_id":"0e698bf4-a869-4710-8167-df680fe3d895","resolution":{"observed_at":"2026-05-16T01:17:04.238867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Simple baselines for image restoration","venue":null,"work_id":"41ace097-9744-42b2-a4d0-0896535d6371","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:562bd24c38d4f87d35a0bba307d8d5b335ca4295b4a2d9347ac680e6681b06d4","observation_id":"92e84447-06d2-4cd4-b831-4b7cce3fb52e","resolution":{"observed_at":"2026-05-16T01:17:04.254430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"InstructIR: High-quality image restoration following human instructions","venue":null,"work_id":"d236a4da-4785-47af-b9ae-8591e3c01bd8","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:1add2cfd78ca27585f1a34db7aac8ee759b04acefc379e09a9359e29b5bd6879","observation_id":"10d1e2b1-0528-4550-832b-3c59d0c7399a","resolution":{"observed_at":"2026-05-16T01:17:04.202383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.09670","last_updated":"2021-10-31T20:03:39Z","snapshot_observed_at":"2026-07-06T10:05:50.314212Z","submitted_at":"2020-10-19T17:06:18Z","title":"RobustBench: a standardized adversarial robustness benchmark","version":3},"cited_work":{"arxiv_id":"2010.09670","doi":"10.48550/arxiv.2010.09670","metadata_source":"arxiv_reference","pith_arxiv_id":"2010.09670","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Robustbench: a stan- dardized adversarial robustness benchmark","venue":"arXiv (Cornell University)","work_id":"8ae4b2b2-a2da-4900-9021-ad64ae1b860f","year":2010},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2010.09670","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:c0ec100f09785f5ad82189e8bb276549cf3d9c4a2a55a662e189b66f83e4f705","observation_id":"5bf49dc7-9ce0-4e08-9cc4-03dca570b9f2","resolution":{"observed_at":"2026-05-11T00:50:49.859450Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Image denoising by sparse 3-D transform-domain collaborative filtering.IEEE Transactions on Image Processing, 16(8):2080–2095","venue":null,"work_id":"8c841ef0-6f1c-4dc3-b886-58827a831ded","year":2080},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:b01e23dd1fcdb147cd81794d588905d557b725120ffe34b091751052175cf4b2","observation_id":"3ee449fa-14f0-46b1-9632-6674096a4b75","resolution":{"observed_at":"2026-05-16T01:17:04.285285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2410.14038","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sliding puzzles gym: A scalable benchmark for state representation in visual reinforcement learning","venue":null,"work_id":"bb1aa3eb-e03a-4847-8917-d555a692b8cb","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:88e48e2aefe8edd27ca3d757369f52a9268781982c2fce73a619dfff46ebb61f","observation_id":"e1dee9c7-3b67-43d0-8373-37a617be1d3e","resolution":{"observed_at":"2026-05-11T00:50:49.864382Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"MambaIR: A simple baseline for image restoration with state-space model","venue":null,"work_id":"f240a784-3235-4838-b26c-9a53cd4543ac","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:01c4d4277d962adcbd1ae7a16d7797d91630b5d4ae5cd61a079d69100b21a03b","observation_id":"44c0a977-f8c2-4f45-ae50-8bb200687718","resolution":{"observed_at":"2026-05-16T01:17:04.126611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Onerestore: A universal restoration framework for composite degradation","venue":null,"work_id":"90a43c95-23f9-4dab-a88f-a0a152d8534d","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:5e8728698b21a6197624a43f72849abce64e283ec4c9fce483aecf3d6b8247a6","observation_id":"a41b98c0-d931-476b-aee4-11f447f886e7","resolution":{"observed_at":"2026-05-16T01:17:04.118537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.20745","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neptune-x: Active x-to-maritime generation for universal maritime object detection","venue":null,"work_id":"82bce95a-7785-43d4-a91b-65b58cce7cdd","year":2025},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:dc4e7f6fa74f05bd56e1751e087f9f62c1412a6a9b1f067c7968e03f1a1d6fd4","observation_id":"8e82df5d-61f9-412b-afa6-84ddf1434e1f","resolution":{"observed_at":"2026-05-11T00:50:49.869283Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Learning latent dynamics for planning from pixels","venue":null,"work_id":"2436e554-ef32-47d8-b221-543c15702eee","year":2019},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:265a97663ae0cb40e9b0a027407ea76cb779dcd260b732e086250de24b335534","observation_id":"fdfe76ab-2a67-4626-ab20-2e847d28866b","resolution":{"observed_at":"2026-05-16T01:17:04.185631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.04104","last_updated":"2024-04-17T17:41:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-01-10T18:12:16Z","title":"Mastering Diverse Domains through World Models","version":2},"cited_work":{"arxiv_id":"2301.04104","doi":"10.1126/sciadv.adu2488","metadata_source":"pith","pith_arxiv_id":"2301.04104","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mastering Diverse Domains through World Models","venue":"cs.AI","work_id":"6aeb260f-8c7c-4f9c-b98b-067cd7c59acd","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2301.04104","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:4a36a95dfa33806766ace256e20d3a2b3a6e3dd1630a6d98ee89534803e97b36","observation_id":"4afed674-590c-4c4f-af90-f8b96462b3e3","resolution":{"observed_at":"2026-05-11T09:08:22.800194Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Dsp-reg: Domain-sensitive parameter regularization for robust domain generalization","venue":null,"work_id":"5aedd873-fb82-4601-9eba-0f6d6e66c3b6","year":2026},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:06505540d7f2e4ea2609c775e3071ffcde4527af435981551f8bb2e27b6dbabd","observation_id":"11354b68-488b-47e5-bdf8-a60c5a7f4e66","resolution":{"observed_at":"2026-05-16T01:17:04.154229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Generalizationinreinforcementlearningbysoftdataaugmentation","venue":null,"work_id":"fa9ce2ef-f353-47c8-8a6f-f7485e6d798d","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:f9e558fc7fdf6b0a24ab0b45ed80185f0492adc960ad496e444f6812fe3addf4","observation_id":"9eba0309-c9a7-4985-9dd5-46e96449c027","resolution":{"observed_at":"2026-05-16T01:17:04.113133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Self-supervised policy adaptation during deployment","venue":null,"work_id":"2bb1faa7-362d-4f08-a356-be553e1290c8","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:f43b0e71bf63f248e1537fbc5d61fd68e7a1938943763d77784d8f68fd97fe73","observation_id":"c4f2244d-8275-4398-ae1a-1ea72f0ae9ef","resolution":{"observed_at":"2026-05-16T01:17:04.210700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Stabilizing deep q-learning with convnets and vision transformersunderdataaugmentation","venue":null,"work_id":"c3dbfaf5-926e-4198-9086-c410d257c48d","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:f13e7c6f32a14d4a224a0c3b345644e0ef8cf160d8d636549b48dc39ca48bcbd","observation_id":"bec98630-2899-4275-a34e-85c2ff93815a","resolution":{"observed_at":"2026-05-16T01:17:04.263157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.16828","last_updated":"2024-03-21T17:56:19Z","snapshot_observed_at":"2026-07-31T05:32:29.431480Z","submitted_at":"2023-10-25T17:57:07Z","title":"TD-MPC2: Scalable, Robust World Models for Continuous Control","version":2},"cited_work":{"arxiv_id":"2310.16828","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.16828","snapshot_observed_at":"2026-07-08T02:04:26.234596Z","title":"TD-MPC2: Scalable, Robust World Models for Continuous Control","venue":"cs.LG","work_id":"360ec5fb-79fd-4490-bc73-3d161609c42d","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2310.16828","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:5408fc6e640c3792513922c4337213fb8b53fe6c3c37989f7fced1691a06c992","observation_id":"c85532a0-dae9-44ea-908f-654792c066e3","resolution":{"observed_at":"2026-05-14T17:27:36.461279Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.12261","last_updated":"2019-03-28T20:56:37Z","snapshot_observed_at":"2026-08-02T09:01:28.869881Z","submitted_at":"2019-03-28T20:56:37Z","title":"Benchmarking Neural Network Robustness to Common Corruptions and Perturbations","version":1},"cited_work":{"arxiv_id":"1903.12261","doi":"10.48550/arxiv.1903.12261","metadata_source":"pith","pith_arxiv_id":"1903.12261","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Benchmarking Neural Network Robustness to Common Corruptions and Perturbations","venue":"cs.LG","work_id":"e28eaed9-7f6b-46ed-ba19-fba407571ba7","year":2019},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/1903.12261","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:92d357a2fd650eb502e758170e4e2e488c93878a48c0594945a23f9fc01e03ca","observation_id":"53981485-eca5-4ad0-a0d1-7fc66002a9d3","resolution":{"observed_at":"2026-05-13T05:02:19.069613Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Agentscodriver: Large language model empowered collaborative driving with lifelong learning","venue":null,"work_id":"dc35f1be-a733-4123-943b-2a29bc33448b","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:8631926c6c5bfe133fb0c21ac0677a0a6e12ad515084acd4df20853f7eba19ac","observation_id":"ad3c6307-dcbc-414d-bf24-bd48226867a7","resolution":{"observed_at":"2026-05-16T01:17:04.072787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"856804f2-9f2b-4780-ba90-b5f5b69f068d","year":2025},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:6ebc507d49df5d7b7bd8764c42a3815ba209e6c8d587be95bbfc12fbbfff8c0b","observation_id":"9f5db8eb-bfa3-4b38-8bdd-f6a60029be66","resolution":{"observed_at":"2026-05-16T01:17:04.105438Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Agentscomerge: Large language model empowered collaborative decision making for ramp merging.IEEE Transactions on Mobile Computing, 24(10):9791–9805","venue":null,"work_id":"3052c9d5-8114-4b8b-8c2d-a46d047f287b","year":2025},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:1e40c4faa7f84f0abae2bf7e2f90a4d7101cb476cf561a5a31255b327ec45580","observation_id":"6a0db5fd-49da-4600-b90f-fa97d6234f73","resolution":{"observed_at":"2026-05-16T01:17:04.245476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.00845","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-01T22:56:21.158598Z","title":"Optimizing agentic reasoning with retrieval via synthetic semantic information gain reward","venue":null,"work_id":"4337776b-86c5-4ac5-97f1-845fd2570b42","year":2026},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:b875d7748b89098f6a6ef0c499add071147b8741442bd4c4d2b9a195bab2fc0a","observation_id":"588f2f27-a26e-4113-bd28-2c793ba86081","resolution":{"observed_at":"2026-05-11T00:50:49.814102Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Planning- oriented autonomous driving","venue":null,"work_id":"4e929fba-025c-47af-80d2-8f4ccb11c8b1","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:c3841b970d8e8f2a16f02d2344d8a765f0319d4578186548fe50e8b1d2a1f71d","observation_id":"cb3252ff-4dd3-4910-b4d3-52da31bcef4c","resolution":{"observed_at":"2026-05-16T01:17:04.168952Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Spectrum random masking for generalization in image-based reinforcement learning","venue":null,"work_id":"542b02a2-1af4-42a5-8c1c-a3a5f23b8ede","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:41dcc994f57f52595fcc67d3482f2276992625de52294fbaccb5703a07f2b557","observation_id":"ab9ca0a6-7e33-490b-994f-22256fc0b3c3","resolution":{"observed_at":"2026-05-16T01:17:04.232126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Adaptive mixtures of local experts.Neural Computation, 3(1):79–87","venue":null,"work_id":"cdb6f518-16d2-4b20-9b6d-d127993b2355","year":1991},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:86eb4703d2af6fa41fc038f4362ac99fdaf2df8ed1b857396adff6f598af6b47","observation_id":"b1df7a0e-fb3e-4fd6-8c21-2242e86ca8d5","resolution":{"observed_at":"2026-05-16T01:17:04.080245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04088","last_updated":"2024-01-08T18:47:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-01-08T18:47:34Z","title":"Mixtral of Experts","version":1},"cited_work":{"arxiv_id":"2401.04088","doi":"10.48550/arxiv.2401.04088","metadata_source":"pith","pith_arxiv_id":"2401.04088","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mixtral of Experts","venue":"cs.LG","work_id":"0de8c352-9daa-4e1e-8c7b-3d0dec69f369","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2401.04088","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:04e4e3a4d0c5c561980b72986340a7b3a5c076cf81309b7ba7f96b22586257c6","observation_id":"e5f61295-f119-479b-a4a5-682d7bb79b19","resolution":{"observed_at":"2026-05-11T00:50:49.811444Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-07-09T08:48:39.110013+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-09T08:48:39.110013+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Hierarchical mixtures of experts and the EM algorithm.Neural Computation, 6(2):181–214","venue":null,"work_id":"3d4b092d-b0e6-4b2f-b18c-35f72eecb9c5","year":1994},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:9e48adbc4aa4a32eb0f3cbcfab933795c8bb1642b24b37abf4f97c8c860cd8a0","observation_id":"9e071edf-101b-44b1-ad73-4035a8e7826c","resolution":{"observed_at":"2026-05-16T01:17:04.280858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"3D common corruptions and data augmentation","venue":null,"work_id":"6f94a14f-8bb8-4719-93f1-5699ac62a720","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:d8dd0c4b4dfc6bb8364d1270acdcaa0fe3acc67d5cdb8cc42f04a081f5932846","observation_id":"e8d19aec-6445-41fd-8ae0-ceb281f7cb80","resolution":{"observed_at":"2026-05-16T01:17:04.140602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09972","last_updated":"2024-10-13T19:24:07Z","snapshot_observed_at":"2026-07-06T19:32:42.378146Z","submitted_at":"2024-10-13T19:24:07Z","title":"Make the Pertinent Salient: Task-Relevant Reconstruction for Visual Control with Distractions","version":1},"cited_work":{"arxiv_id":"2410.09972","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.09972","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Make the pertinent salient: Task-relevant reconstruction for visual control with distractions","venue":null,"work_id":"be325125-ed13-4cd7-9e73-8e052f3cb543","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2410.09972","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:b03c988065a12d24d9cd68bb99f0337d98a17608ae073da577aea6492a0ad16b","observation_id":"9e00b4dc-db98-4baf-9b77-3162c5d548cf","resolution":{"observed_at":"2026-05-11T00:50:49.822024Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.13649","last_updated":"2021-03-07T16:37:37Z","snapshot_observed_at":"2026-08-04T06:44:16.616319Z","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":"2004.13649","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2004.13649","snapshot_observed_at":"2026-07-04T16:19:57.605299Z","title":"Image augmentation is all you need: Regularizing deep reinforcement learning from pixels","venue":null,"work_id":"6ab82ef3-1d38-4b4d-8c39-6077a6c99690","year":2004},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2004.13649","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:124d1a2ece8c566caca28ab214d3c700e686a8bc35c55973c0c201ead1e36295","observation_id":"20e3d31d-9519-4465-99e0-61f169c56f3b","resolution":{"observed_at":"2026-05-11T00:50:49.816695Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"DeblurGAN: Blind motion deblurring using conditional adversarial networks","venue":null,"work_id":"9fddbed7-22a2-4e1f-a5db-6e09357b44d7","year":2018},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:4ae2f02f0c4843026e7ce3eab6720d6931dac8d95f62bfb43aadb7b5e716a64c","observation_id":"fdb8f1e8-c7e1-4aa1-9821-da8cce693f99","resolution":{"observed_at":"2026-05-16T01:17:04.160188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Reinforce- ment learning with augmented data","venue":null,"work_id":"10ed9677-d9f6-430f-97dc-a789fa366dd7","year":2020},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:3dd9bc358e5cc93682c7507e3734c0be7278bd27cb977efc75371c3ff80d4231","observation_id":"3eadffff-4ccb-4f3a-9be6-880358e98037","resolution":{"observed_at":"2026-05-16T01:17:04.194294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"CURL: Contrastive unsupervised representations for reinforcement learning","venue":null,"work_id":"867d830c-45e8-400d-8633-0a330a427c7d","year":2020},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:1618509484e760ad3b786300eff3d3886f2153f0946700779b0355fc43597ad3","observation_id":"1814ca02-6d78-4c8c-a860-1dc77911d33f","resolution":{"observed_at":"2026-05-16T01:17:04.148463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"All-in-one image restoration for unknown corruption","venue":null,"work_id":"7c769e82-bd41-40b6-86ef-d0334c6334db","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:c4ae4f1e292d4e2da097079633cf4227e785e81bfa1d19b6233ebb81817f9424","observation_id":"03316d1c-6fc0-4711-9e1e-e0edb7c301f5","resolution":{"observed_at":"2026-05-16T01:17:04.100276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Instruct2see: Learningtoremoveanyobstructions across distributions","venue":null,"work_id":"33b43e32-0e0b-4269-8692-0629bdc65daa","year":2025},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:d868c11ec1fdd563c84d35698c35f2671f615829edcced6d93ce95e5749dbfc7","observation_id":"701d5e17-7ffd-44a5-9181-064df0974f97","resolution":{"observed_at":"2026-05-16T01:17:04.250207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Policy-independent behavioral metric-based representa- tion for deep reinforcement learning","venue":null,"work_id":"ba5767cf-0dd8-447d-ab10-a47b15de0a47","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:a1e82a4ef39e27f448a4859c1cf22c89bc07e714d7c18c5482f3f412fda37362","observation_id":"21eb2423-f18e-4e0a-b46e-2c0180a8be96","resolution":{"observed_at":"2026-05-16T01:17:04.217838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"MoE-LLaVA: Mixture of experts for large vision-language models.IEEE Transactions on Multimedia","venue":null,"work_id":"2bb65a6b-1a04-407e-b474-cb1bc26ad232","year":2026},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:4e7bfe74f1849086bf6be85cc77cf5ef0ad69e1528f0092a3e63e191cf32462f","observation_id":"966ce11d-5719-4209-9dac-67694fef13ab","resolution":{"observed_at":"2026-05-16T01:17:04.087368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"TTT++: When does self-supervised test-time training fail or thrive? InAdvances in Neural Information Processing Systems (NeurIPS), volume 34, pages 21808–21820","venue":null,"work_id":"2d08866f-5846-45f8-a5f9-0e700bf27311","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:f383cec9bc34b5edcdfc36e210b556204f51a768bd16feb9a8a2ec2dd736d6e5","observation_id":"6e1097f5-9ef8-48e2-9a0f-9c3c63a2f334","resolution":{"observed_at":"2026-05-16T01:17:04.225083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Gustafsson, Zheng Zhao, Jens Sjölund, and Thomas B","venue":null,"work_id":"34ed93f7-53fd-4068-ae73-9a1ce90364ea","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:fcb7c3dc998d19e659bddeb57ba0808a7bd1af5c74c6f7fdfe8704bd5c59a7c9","observation_id":"4195e165-a477-42dd-a514-ad172a6433a4","resolution":{"observed_at":"2026-05-16T01:17:04.276197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.00588","last_updated":"2023-03-01T09:21:14Z","snapshot_observed_at":"2026-07-06T13:47:58.509110Z","submitted_at":"2022-09-01T17:03:07Z","title":"Transformers are Sample-Efficient World Models","version":2},"cited_work":{"arxiv_id":"2209.00588","doi":"10.48550/arxiv.2209.00588","metadata_source":"arxiv_reference","pith_arxiv_id":"2209.00588","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Transform- ers are sample-efficient world models.arXiv preprint arXiv:2209.00588","venue":"arXiv (Cornell University)","work_id":"388af2ed-cc43-48cc-92be-9fba2c20d9e3","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2209.00588","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:ba40a6bdd650aeba187a4e8b2accb0f9df03abcb806c4c43c21332805c63c3eb","observation_id":"b04c5e12-280f-4e81-8978-b5c05e03c7cf","resolution":{"observed_at":"2026-05-11T00:50:49.829546Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Human-level control through deep reinforcement learning.Nature, 518(7540):529–533","venue":null,"work_id":"ebe8893f-6bc8-4ba9-8919-606e02a11c77","year":2015},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:2af56a71a8f8272b0d8f55118f2187e6895da77b9511d6f627f1ef37041a8931","observation_id":"bd4bd978-8836-4dff-9ff1-5b948341418c","resolution":{"observed_at":"2026-05-16T01:17:04.267079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13816","last_updated":"2025-02-24T21:05:58Z","snapshot_observed_at":"2026-08-05T20:44:16.574781Z","submitted_at":"2024-10-17T17:46:26Z","title":"Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance","version":2},"cited_work":{"arxiv_id":"2410.13816","doi":"10.48550/arxiv.2410.13816","metadata_source":"pith","pith_arxiv_id":"2410.13816","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Nakamoto, O","venue":"cs.RO","work_id":"e3d9b3e2-4c9a-409f-bb52-384cff83db09","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2410.13816","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:af76b2c4d1c18b6662c72cf3491e449652e9b13eae9fce3776566e04d18e1745","observation_id":"707986f2-bb99-456f-9771-85806412c125","resolution":{"observed_at":"2026-05-11T00:50:49.832076Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Dmc-vb: A benchmark for representation learning for control with visual distractors.Advances in Neural Information Processing Systems, 37:6574–6602","venue":null,"work_id":"4f11adeb-265b-42b4-851d-3d529d2d6b00","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:fb49aabe8d87ec1951bf7ca171f48c67e3e0d2af7b45d0269331aee5f6f824aa","observation_id":"60b5b844-78e4-4484-8961-69eea778f6c6","resolution":{"observed_at":"2026-05-16T01:17:04.258619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Model-based rein- forcement learning with isolated imaginations.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(5):2788–2803","venue":null,"work_id":"246ec781-c37c-406a-be5a-c62696de5a06","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:5fca5455965c74fa163bd1856edaa7e26938aa271db7cbb393c820f9a4fdd0ed","observation_id":"e34e76ca-322e-453d-9d2e-5350d653c5c3","resolution":{"observed_at":"2026-05-16T01:17:04.271463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"PromptIR: Prompting for all-in-one blind image restoration","venue":null,"work_id":"e2e9a52f-d3a2-43f5-862e-1ead4c259db7","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:14f466af47ac002173b441db4d5a824b4dc23e500c114945c9acfa41a44e9c74","observation_id":"4577c2da-b8fb-4999-809b-b1b8bd1b62f7","resolution":{"observed_at":"2026-05-16T01:17:04.093011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00951","last_updated":"2024-05-27T11:44:51Z","snapshot_observed_at":"2026-08-04T22:30:49.675313Z","submitted_at":"2023-08-02T05:20:55Z","title":"From Sparse to Soft Mixtures of Experts","version":2},"cited_work":{"arxiv_id":"2308.00951","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00951","snapshot_observed_at":"2026-07-04T15:39:56.509576Z","title":"From sparse to soft mixtures of experts","venue":null,"work_id":"231d2f62-bb2f-4331-ae5d-1fd92c1a1ff3","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2308.00951","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:c52292eb3bb6a1b1cf02621fba0e002f29617da5d0966624d55d52844b04054d","observation_id":"b9bc0e76-6ccb-4ee0-b25f-d30dad3295d0","resolution":{"observed_at":"2026-05-11T00:50:49.837183Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.08191","last_updated":"2024-05-28T00:37:02Z","snapshot_observed_at":"2026-08-05T06:18:26.955637Z","submitted_at":"2024-02-13T03:25:33Z","title":"THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation","version":2},"cited_work":{"arxiv_id":"2402.08191","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.08191","snapshot_observed_at":"2026-07-04T06:39:37.218470Z","title":"The colosseum: A benchmark for evaluating generalization for robotic manipulation","venue":null,"work_id":"02291732-92d3-42f2-b15d-fddd5616baec","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2402.08191","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:87b1e58b8c5a66ddb65785d3d4584da2d2a2a1a4cedcaecc8980d8366e2aba41","observation_id":"fbcd5f85-19e1-4fb1-8366-2d096f6405bf","resolution":{"observed_at":"2026-05-11T00:50:49.834661Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"MoE-DiffIR: Task-customized diffusion priors for universal compressed image restoration","venue":null,"work_id":"3562661e-d85c-4a6d-94f2-483c2a29e877","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:3aaba1eca547b42b6b1d58eee49f1e2e93c67f85f9e0acd0f90809561b7d0882","observation_id":"f944368a-7b90-48de-9160-dfd336fc0650","resolution":{"observed_at":"2026-05-16T01:17:04.177894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Scaling vision with sparse mixture of experts","venue":null,"work_id":"01bf5c12-5670-40da-b2f9-056d5b633e40","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:198a5db86ac00ef0a299fc6eb815dc77590e7a6677c606655b359d2425133613","observation_id":"e14ba872-07a0-4cd6-8843-c6fd299a4246","resolution":{"observed_at":"2026-05-16T01:17:04.041858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.07109","last_updated":"2023-03-13T13:43:59Z","snapshot_observed_at":"2026-07-06T15:02:36.621143Z","submitted_at":"2023-03-13T13:43:59Z","title":"Transformer-based World Models Are Happy With 100k Interactions","version":1},"cited_work":{"arxiv_id":"2303.07109","doi":"10.48550/arxiv.2303.07109","metadata_source":"arxiv_reference","pith_arxiv_id":"2303.07109","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Transformer-based world models are happy with 100k interactions","venue":"arXiv (Cornell University)","work_id":"247a412b-2e1d-48e2-afc6-40c6752b6188","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2303.07109","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:607c2a88ac14915ca1aafff7d3f6fa7f03558888e8407d7934aa420fa96fdebb","observation_id":"8d0968d7-4181-4ab4-818e-6482f0d2219a","resolution":{"observed_at":"2026-05-11T00:50:49.866789Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"U-Net: Convolutional networks for biomedical image segmentation","venue":null,"work_id":"25b37dd8-2e0e-49b7-b956-17df6be98efe","year":2015},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:46b36473ec4e59f71256e06b9b41bc45086e811af6768c6c0e55a1320df2b185","observation_id":"99480702-f663-47a1-b763-abd256506ce8","resolution":{"observed_at":"2026-05-16T01:17:04.047403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Outrageously large neural networks: The sparsely-gated mixture-of-experts layer","venue":null,"work_id":"29395336-5767-4d13-94a7-28bb2dddcf20","year":2017},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:55d61880c17fbe7b30871f6b93d8c80dffaa5015e6b90599e7c43d1f2049dacc","observation_id":"c17e8eee-1739-4df7-9b19-ffdc7341779b","resolution":{"observed_at":"2026-05-16T01:17:03.998735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"DriveX: Omni scene modeling for learning generalizable world knowledge in autonomous driving","venue":null,"work_id":"9f9d48c8-6e1e-4e97-bef5-13f1ff74644a","year":2025},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:3f69b2706330044ef71cc9d232840590b2452b685a489c4a74a9e73923832906","observation_id":"2b30b1a2-ec91-4e48-b39a-aebcc74e2caf","resolution":{"observed_at":"2026-05-16T01:17:04.004910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"A simple framework for generalization in visual RL under dynamic scene perturbations","venue":null,"work_id":"73a9e507-511b-4670-8d9c-cfd9e64d0867","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:52aa65a800c88a752e33817056b6560bbdde8feec6e8b996c15c260237b7dd19","observation_id":"3594b574-0ccc-4fd0-ad81-a515dd7998b5","resolution":{"observed_at":"2026-05-16T01:17:03.933523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.02722","last_updated":"2021-01-07T19:03:34Z","snapshot_observed_at":"2026-08-05T19:26:49.355781Z","submitted_at":"2021-01-07T19:03:34Z","title":"The Distracting Control Suite -- A Challenging Benchmark for Reinforcement Learning from Pixels","version":1},"cited_work":{"arxiv_id":"2101.02722","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2101.02722","snapshot_observed_at":"2026-06-30T06:04:21.445585Z","title":"The distracting con- trol suite–a challenging benchmark for reinforcement learning from pixels","venue":null,"work_id":"7c44b6cc-a81e-4b09-a5f8-1c5eaf968cc8","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2101.02722","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:cdbfce5378931989ae93fde73a9b9f13787deaac4a2417c18c87c74a02d82411","observation_id":"812b0d40-8f73-419a-8b48-16694bf1976f","resolution":{"observed_at":"2026-05-11T00:50:49.847065Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.06263","last_updated":"2024-05-30T09:40:02Z","snapshot_observed_at":"2026-07-06T18:12:26.233112Z","submitted_at":"2024-05-10T06:28:42Z","title":"Learning Latent Dynamic Robust Representations for World Models","version":2},"cited_work":{"arxiv_id":"2405.06263","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.06263","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning latent dynamic robust representations for world models","venue":null,"work_id":"da389d88-b11a-4501-bad5-1ad73de71996","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2405.06263","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:bd391640ba64cae1532cda0bad005bbc1ef10905de9da780680747a24bf8d62d","observation_id":"26411a1f-80c4-4ddf-b11c-7dc6c85b94e3","resolution":{"observed_at":"2026-05-11T00:50:49.871710Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.04482","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T21:33:58.821140Z","title":"Proagentbench: Evaluating llm agents for proactive assistance with real-world data","venue":null,"work_id":"f1f8054c-4774-4c8c-be2f-d5a1ad576cbf","year":2026},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:042660a44330a95296e8a51323508950c21b88b7931a5040a851b7c72d1a8ce1","observation_id":"7a569f5c-4fd3-4191-85f0-5bea4c39fa74","resolution":{"observed_at":"2026-05-11T00:50:49.854513Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"1801.00690","doi":"10.48550/arxiv.1801.00690","metadata_source":"pith","pith_arxiv_id":"1801.00690","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepMind Control Suite","venue":"cs.AI","work_id":"54294ef0-c651-4d5a-a72b-f85a88329a71","year":2018},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/1801.00690","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:1c1f4b0777b036ebf0246f177416d6fba5d36eecd743f606b2378ffa4034247d","observation_id":"9f50ade1-6702-4695-8ced-623df608ca23","resolution":{"observed_at":"2026-05-13T07:44:14.794093Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Focus-Then-Reuse: Fast adaptation in visual perturbation environments","venue":null,"work_id":"e95764d3-f2df-4fbb-8dd6-092df5f428c7","year":2025},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:61d7c16d5f55df3c854131d01a4378042fda3c73302a2969e270ed102201517b","observation_id":"8ae1fe59-7420-4a4c-9f15-705e86a30457","resolution":{"observed_at":"2026-05-16T01:17:03.941345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"GridFormer: Residual dense transformer with grid structure for image restoration in adverse weather conditions.International journal of computer vision, 132(10):4541–4563","venue":null,"work_id":"b583b477-77ff-48be-90d6-d821d055ac10","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:547a50747a20c8d9793c1c302d4e71b8d45bd54888982d4dbefb651125ad6ecf","observation_id":"401f7ed3-bc6b-4fe3-a367-2f3fdac2b9d0","resolution":{"observed_at":"2026-05-16T01:17:03.992541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"DriveDreamer: Towards real-world-driven world models for autonomous driving","venue":null,"work_id":"40688f12-5718-4ce0-b707-663058e28ece","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:920bf05eaf7eed01ecead7d9222bda4437bf99ca2f7d6bee3bccb3142932d085","observation_id":"c9c883d2-da64-460a-af30-3ec9e10f4053","resolution":{"observed_at":"2026-05-16T01:17:04.010849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17116","last_updated":"2023-12-28T16:53:23Z","snapshot_observed_at":"2026-07-06T17:09:19.909685Z","submitted_at":"2023-12-28T16:53:23Z","title":"Generalizable Visual Reinforcement Learning with Segment Anything Model","version":1},"cited_work":{"arxiv_id":"2312.17116","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.17116","snapshot_observed_at":"2026-07-02T16:07:08.245059Z","title":"Generalizable visual reinforcement learning with segment anything model","venue":null,"work_id":"590b0931-5fdd-4c9d-ae2d-1671b531b8c4","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2312.17116","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:ecf9114166ae9956cb723724015103d08740c548a77485b4c6fba464a100996e","observation_id":"e9293812-fa2f-4029-b0cf-6a7886a952df","resolution":{"observed_at":"2026-05-11T00:50:49.849509Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"DiffIR: Efficient diffusion model for image restoration","venue":null,"work_id":"b0826df5-a0f8-4cec-b0df-bd66c6708593","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:edfd8fbf964644a2c75f529a75c93ddab269ec831685dc4b3c2694652bc3d9db","observation_id":"a0448c6a-0583-4c84-96cd-a411ba0d6fbe","resolution":{"observed_at":"2026-05-16T01:17:04.066172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Image de-raining transformer.IEEE transactions on pattern analysis and machine intelligence, 45(11):12978–12995","venue":null,"work_id":"ce2cb1b5-2a76-4d8b-b3f3-0767934b06e9","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:4cc120128da07987bdfdbf7cee0e5e5e2e69a0828a50357b13af545270fb7112","observation_id":"a16077da-159b-4f58-abce-6bfb3eb7e752","resolution":{"observed_at":"2026-05-16T01:17:03.946760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.19668","last_updated":"2024-02-14T03:56:25Z","snapshot_observed_at":"2026-07-06T16:40:35.590974Z","submitted_at":"2023-10-30T15:50:56Z","title":"DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization","version":2},"cited_work":{"arxiv_id":"2310.19668","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2310.19668","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"DrM:Mastering visual reinforcement learning through dormant ratio minimization","venue":null,"work_id":"867565cf-af09-4427-8526-b8262eb57de1","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2310.19668","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:1c79522fd8dd9494014f733b6fdf0f82a86dc856e603aa028377cc94c64783d1","observation_id":"f6fc8ad4-a7f3-4c12-bc63-ee0b631429fb","resolution":{"observed_at":"2026-05-11T00:50:49.824477Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06114","last_updated":"2024-09-26T17:14:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-09T19:42:22Z","title":"Learning Interactive Real-World Simulators","version":3},"cited_work":{"arxiv_id":"2310.06114","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.06114","snapshot_observed_at":"2026-07-04T17:09:59.117795Z","title":"Learning Interactive Real-World Simulators","venue":"cs.AI","work_id":"16f38691-7ab6-4e23-bba5-6b656579e579","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2310.06114","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:00909ec90338aa31a1ff4eed58a8d07723f43bff08f33b29da59a4f24101b80a","observation_id":"3eb70ba7-d5e0-4e47-a1bb-76578f8ece4f","resolution":{"observed_at":"2026-05-16T02:15:18.951679Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.09645","last_updated":"2021-07-20T17:29:13Z","snapshot_observed_at":"2026-07-06T11:30:56.150751Z","submitted_at":"2021-07-20T17:29:13Z","title":"Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"2107.09645","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2107.09645","snapshot_observed_at":"2026-07-04T07:59:40.482533Z","title":"Yarats, R","venue":null,"work_id":"15c4c6c3-a4fd-4b37-97d1-7e67f55a3eef","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2107.09645","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:03a6b5a2ea044b9b2fab626028166c4e19214fa7c6c94ac06d321151c4e66540","observation_id":"72f3cd49-cf92-4d66-8876-a92ffa4a7854","resolution":{"observed_at":"2026-05-11T00:50:49.842269Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.02029","last_updated":"2026-06-05T06:21:20Z","snapshot_observed_at":"2026-07-30T23:04:23.206455Z","submitted_at":"2026-04-02T13:36:37Z","title":"The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook","version":2},"cited_work":{"arxiv_id":"2604.02029","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.02029","snapshot_observed_at":"2026-07-09T05:36:01.166323Z","title":"The latent space: Foundation, evolution, mechanism, ability, and outlook.arXiv preprint arXiv:2604.02029","venue":"cs.AI","work_id":"66adad9d-c3df-4cf7-9601-cf9d67d19ef5","year":2026},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2604.02029","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:ca664809442437fc38de84409664a1cd5c278a999228ac363853bebd443d4123","observation_id":"ba8fda6c-403f-4503-af0f-fafcac45d4ec","resolution":{"observed_at":"2026-06-08T02:03:55.088792Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Pre- trained image encoder for generalizable visual reinforcement learning.Advances in Neural Information Processing Systems, 35:13022–13037","venue":null,"work_id":"d98a5c9e-d12e-4f7d-9e83-bf9ff0a74eef","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:ee38d9a3db47230c190626af0d2b7bb500946476a99ae6048c6ddeb7d3615cbd","observation_id":"1f9c2d3f-dc26-4f91-848b-9d448321e715","resolution":{"observed_at":"2026-05-16T01:17:03.982071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Rl-vigen: Areinforcement learning benchmark for visual generalization.Advances in Neural Information Processing Systems, 36: 6720–6747","venue":null,"work_id":"70154dd2-369c-4f72-986b-37ce0be1418a","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:20182080c63eb6b96cb4923a8b7a40b392b92dee594166164a7b743965abcf02","observation_id":"f4373cdf-e957-462b-83a6-a69e68f38c48","resolution":{"observed_at":"2026-05-16T01:17:04.059801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Restormer: Efficient transformer for high-resolution image restoration","venue":null,"work_id":"318f998f-8879-44d8-b90b-bc0fe2e351b6","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:2b04c307a3541aed0cf634ba93b571674beb383e583ff610809386c290fe6c27","observation_id":"1bba4166-1749-4fa6-82f5-d1c0a2297c8d","resolution":{"observed_at":"2026-05-16T01:17:04.053421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Learning invariant representations for reinforcement learning without reconstruction","venue":null,"work_id":"74d6cbd7-5048-4efd-a234-556f465e416b","year":2021},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:80b2a3550f3f0cb9675476b9b6bd935c61ddfdf04a9a196cc0d7127d5cc6575d","observation_id":"41153a18-fd0e-4a4b-ba55-b66a049159ee","resolution":{"observed_at":"2026-05-16T01:17:03.976695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Focus On What Matters: Separated models for visual-based rl generalization.Advances in Neural Information Processing Systems, 37:116960–116986","venue":null,"work_id":"96e3d3e7-c5ff-4794-842c-3a37c99de784","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:82657f20d3d058fdc9774b424d11662ae3ea764ce7f220ad615cd58727e5ed95","observation_id":"13bfaada-3c94-4ac6-905e-68ac7850f840","resolution":{"observed_at":"2026-05-16T01:17:03.987399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Image de-raining using a conditional generative adversarial network.IEEE transactions on circuits and systems for video technology, 30(11):3943–3956","venue":null,"work_id":"b139857c-b691-429e-97b8-c390c31f4e30","year":2019},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:2ff7cac7c9a4331cb474197df74be71c9454fd288cecbeba0e147f931867e9e0","observation_id":"99353826-f1eb-4fd4-bf00-57ae2b3067fc","resolution":{"observed_at":"2026-05-16T01:17:04.018152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"STORM: Efficient stochastic transformer based world models for reinforcement learning.Advances in Neural Information Processing Systems, 36:27147–27166","venue":null,"work_id":"b278c993-7ea2-4b58-9a39-81f90ab7ebff","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:70d1e4a068696910519d56db9b56dfaad9b33214db6eba49a0bb76e50e9f5e65","observation_id":"9431598d-80f3-4d46-87a4-ea66f69ebcac","resolution":{"observed_at":"2026-05-16T01:17:03.970351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Perceive-IR: Learning to perceive degradation better for all-in-one image restoration.IEEE Transactions on Image Processing","venue":null,"work_id":"8eb2a4da-3346-4660-983f-b3034e19033a","year":2025},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:cc98cfbbc7991f2ac0c46034790588ec10ab4b4e4804c315aa738ba5360b37dd","observation_id":"af4119c5-29ca-41c2-8e43-67e8e6236d55","resolution":{"observed_at":"2026-05-16T01:17:04.034829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"SAC Flow: Sample-efficient reinforcement learning of flow-based policies via velocity-reparameterized sequential modeling","venue":null,"work_id":"2a4b265d-4ff9-46cc-8b12-494bfd148d80","year":2026},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:937913806d29c0d6c871bc15b8b6ac5ca81dfe1e91fe051b87f36fee8f92dcf1","observation_id":"bd7e6aaa-de52-4be7-a024-7b32b912918c","resolution":{"observed_at":"2026-05-16T01:17:03.952866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"TACO: Temporal latent action-driven contrastive loss for visual reinforcement learning","venue":null,"work_id":"48c22791-08c5-4a3c-ab30-a02eb5398e1e","year":2023},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:678c30209fe49659c386eb2c700cb7c05eb359ff0b093f31c476d1ecd8304628","observation_id":"510d052e-f34b-48d3-8aa0-fb35768e7d63","resolution":{"observed_at":"2026-05-16T01:17:03.964353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"OccWorld: Learning a 3D occupancy world model for autonomous driving","venue":null,"work_id":"eec2c6fe-6621-40d4-a009-eb8f904a8c1a","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:2c5ca29355741145f4d1f19b4027710a3b68bf1252f333e7f158c96df01a2dc7","observation_id":"667e0c8b-a3c6-486b-b87c-0e3a9e5e7b8b","resolution":{"observed_at":"2026-05-16T01:17:04.026586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04983","last_updated":"2025-02-01T02:40:49Z","snapshot_observed_at":"2026-07-06T19:46:54.707852Z","submitted_at":"2024-11-07T18:54:37Z","title":"DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning","version":2},"cited_work":{"arxiv_id":"2411.04983","doi":"10.48550/arxiv.2411.04983","metadata_source":"pith","pith_arxiv_id":"2411.04983","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning","venue":"cs.RO","work_id":"4a946586-a786-46da-9388-197c5410bf39","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2411.04983","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:284bdd3c0f4abdfa66f7768ab947530388c3cfc40001cdccf987cd2a4743e06b","observation_id":"8079df82-f603-4666-a03a-c6ea86967a91","resolution":{"observed_at":"2026-05-17T16:06:10.055251Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-07-11T22:49:30.554473+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T22:49:30.554473+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12377","last_updated":"2024-04-18T17:58:03Z","snapshot_observed_at":"2026-08-02T11:29:41.147175Z","submitted_at":"2024-04-18T17:58:03Z","title":"RoboDreamer: Learning Compositional World Models for Robot Imagination","version":1},"cited_work":{"arxiv_id":"2404.12377","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12377","snapshot_observed_at":"2026-07-10T11:47:02.936864Z","title":"RoboDreamer: Learning Compositional World Models for Robot Imagination","venue":"cs.RO","work_id":"b1231baa-7c16-4ecf-a6a8-ef49d0875212","year":2024},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2404.12377","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:b75adebe668a18531634387fe8cc121e9f52a597a9f71e127ff217b182eeb153","observation_id":"1aa5e06a-914e-4268-9983-80b05a44883c","resolution":{"observed_at":"2026-05-15T20:47:30.400020Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-06-05T21:23:00.469572Z","title":"Uni-Perceiver-MoE: Learning sparse generalist models with conditional moes.Advances in Neural Information Processing Systems, 35:2664–2678","venue":null,"work_id":"c8db510e-6faa-4171-9162-bd72afaff7bb","year":2022},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:fc29dae5a6ffc266b16f50c1bb3027420c5b6f3ac07f5ee63c208a48904ca0cb","observation_id":"16be3768-a413-4804-ba88-da44e27a823e","resolution":{"observed_at":"2026-05-16T01:17:03.958937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.12293","last_updated":"2025-01-18T02:57:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-09-25T15:32:31Z","title":"robosuite: A Modular Simulation Framework and Benchmark for Robot Learning","version":3},"cited_work":{"arxiv_id":"2009.12293","doi":null,"metadata_source":"pith","pith_arxiv_id":"2009.12293","snapshot_observed_at":"2026-07-10T23:07:48.196994Z","title":"robosuite: A Modular Simulation Framework and Benchmark for Robot Learning","venue":"cs.RO","work_id":"d616d4ba-7713-4e3e-8c9e-dfebbb8f1abf","year":2020},"citing_paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations","version":3},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-05-11T00:48:43.992238Z"},"links":{"cited_paper":"/paper/2009.12293","citing_paper":"/paper/2604.24661"},"observation_digest":"sha256:b3fd45df442d54d7bd9c3423507d1cbaa14e8162336f353a8f43c08478c7f0b8","observation_id":"4589fd75-7c7c-43fb-9b77-f995f161d4dd","resolution":{"observed_at":"2026-05-12T22:37:13.523094Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.24661","last_updated":"2026-05-08T02:03:01Z","latest_version":3,"primary_category":"cs.RO","snapshot_observed_at":"2026-07-06T23:10:38.548416Z","submitted_at":"2026-04-27T16:24:40Z","title":"Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations"},"reference_resolution":{"displayed":83,"state_counts":{"malformed_identifier":1,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":1,"verified_exact":24,"verified_fuzzy":55},"total_outbound_references":83},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 4 inbound Pith citation observations for arXiv:2604.24661."}