{"as_of":"2026-08-05T13:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b0b25d191ace8ec564b95a9b564a138946f0179ec182e14ec6f9e6762714d738","coverage":[{"denominator":21,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-18T12:48:32.123998Z","state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":31,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T09:43:32.425225Z","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":"2026-07-10T08:36:59.803669Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-08-03T03:56:47.187007Z","title":"World-env: Leveraging world model as a virtual environment for vla post-training","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.06508","last_updated":"2026-05-25T03:56:37Z","snapshot_observed_at":"2026-08-03T03:56:46.452714Z","submitted_at":"2026-02-06T08:57:55Z","title":"World-VLA-Loop: Closed-Loop Learning of Video World Model and VLA Policy","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T03:56:47.187007Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2602.06508"},"observation_digest":"sha256:009eeef81de79d4664f39f0c0252c13b2ca57fdc8e6e8aff2affe2cb570cb1bb","observation_id":"a39f2f28-0a23-48f3-ac3b-d2a29ee85cd3","resolution":{"observed_at":"2026-08-03T03:56:47.187007Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2602.06949","last_updated":"2026-02-06T18:49:43Z","snapshot_observed_at":"2026-07-06T22:44:51.126114Z","submitted_at":"2026-02-06T18:49:43Z","title":"DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos","version":1},"reference_index":104,"source":"pdf_text","source_observed_at":"2026-05-16T17:02:33.997887Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2602.06949"},"observation_digest":"sha256:9990ae487e3ed7acea6cdf48214c9f304e426de79bc0fd4f50cf7a6a438d33f4","observation_id":"5c99e8dc-5061-4671-9e79-1eb6ca5d2a40","resolution":{"observed_at":"2026-05-16T17:02:34.219230Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2602.10503","last_updated":"2026-05-16T03:35:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-02-11T04:05:03Z","title":"Towards Long-Lived Robots: Continual Learning VLA Models via Reinforcement Fine-Tuning","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-21T14:07:10.387869Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2602.10503"},"observation_digest":"sha256:815a587651ae16bcd2d6b4699ab5c1020703da632923e91e9cbd23cfcc7270b9","observation_id":"3bdffa80-5c52-44b7-9884-71a137853a13","resolution":{"observed_at":"2026-05-21T14:10:13.361844Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-08-02T23:23:52.562350Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.13977","last_updated":"2026-06-27T16:11:05Z","snapshot_observed_at":"2026-08-02T23:23:50.481908Z","submitted_at":"2026-02-15T03:48:20Z","title":"WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T23:23:52.562350Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2602.13977"},"observation_digest":"sha256:4d1fb7f3506736ea62b7e8341ac5542bc39c8a8e270f96a4fab0957d9d7c4c84","observation_id":"58196975-9998-4025-9842-2eca9a277942","resolution":{"observed_at":"2026-08-02T23:23:52.562350Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2602.18532","last_updated":"2026-05-20T07:29:11Z","snapshot_observed_at":"2026-08-02T03:49:48.311375Z","submitted_at":"2026-02-20T09:26:17Z","title":"VLANeXt: Recipes for Building Strong VLA Models","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-21T12:58:30.777235Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2602.18532"},"observation_digest":"sha256:57aac44defc06a7e8e1a8f8e78ff0ad8273cb433d2ad06f80874192396541519","observation_id":"71c88fad-a9b5-4a7f-b2be-7ada6c9808c1","resolution":{"observed_at":"2026-05-21T13:00:09.868211Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2603.28489","last_updated":"2026-07-04T13:25:12Z","snapshot_observed_at":"2026-08-05T11:17:52.410204Z","submitted_at":"2026-03-30T14:23:45Z","title":"Video Generation Models as World Models: Efficient Paradigms, Architectures and Algorithms","version":2},"reference_index":206,"source":"pdf_text","source_observed_at":"2026-05-14T01:35:14.878069Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2603.28489"},"observation_digest":"sha256:f2a1fd1f4ff923d5c1d46aeef7babd099eeacdb178025a6af50114c898169050","observation_id":"3663fc50-efd7-4ecf-8058-96f63c15af24","resolution":{"observed_at":"2026-05-14T01:38:35.951488Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2604.14732","last_updated":"2026-04-19T07:53:54Z","snapshot_observed_at":"2026-07-06T23:02:27.141640Z","submitted_at":"2026-04-16T07:46:05Z","title":"World-Value-Action Model: Implicit Planning for Vision-Language-Action Systems","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T11:25:57.218073Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2604.14732"},"observation_digest":"sha256:f36a938716eeb531d5e03fe87ce757fe3bc7af7b07158ab7902176f446fdabfc","observation_id":"f69f81ce-1e58-498d-8456-ff24ecd6251e","resolution":{"observed_at":"2026-05-10T11:30:19.058538Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2604.21741","last_updated":"2026-05-05T16:01:35Z","snapshot_observed_at":"2026-07-29T22:30:00.899443Z","submitted_at":"2026-04-23T14:42:54Z","title":"Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-09T21:26:26.540403Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2604.21741"},"observation_digest":"sha256:aa26651d763a35c2f741f2f65499947c3fca3a30d07dca0c6fcc0ffe85f585fd","observation_id":"9df8fdc2-0534-4963-84c2-95e4ddce97df","resolution":{"observed_at":"2026-05-11T14:36:07.495875Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.07931","last_updated":"2026-05-13T19:21:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-08T16:04:43Z","title":"One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-11T03:39:41.090350Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.07931"},"observation_digest":"sha256:7811938000458e7c187d23dee7f767eaccbb7f1164c21379cc58f4eea8c44c4b","observation_id":"5eba779d-c681-40df-8d51-8d7a23f4a924","resolution":{"observed_at":"2026-05-11T03:40:53.563722Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.07931","last_updated":"2026-05-13T19:21:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-08T16:04:43Z","title":"One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-12T02:53:54.608425Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.07931"},"observation_digest":"sha256:74ede7d1d1177cbc9bd424af4208b68e74acf6430d854cfd7b62a91742cbb8b9","observation_id":"663c2bd7-4df7-4f41-83ef-9783a5cd42dd","resolution":{"observed_at":"2026-05-12T07:26:29.140872Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.07931","last_updated":"2026-05-13T19:21:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-08T16:04:43Z","title":"One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-15T06:16:48.180290Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.07931"},"observation_digest":"sha256:be93fe626a3b3ae98b7b8aa589c6d40a4f1d80290d3f105dbafb3887c95d7c33","observation_id":"0dbd37a9-7ff7-496a-84d2-00cf0e3eed21","resolution":{"observed_at":"2026-05-15T06:19:49.821725Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.10819","last_updated":"2026-05-13T09:16:02Z","snapshot_observed_at":"2026-08-04T23:42:58.419847Z","submitted_at":"2026-05-11T16:37:07Z","title":"ALAM: Algebraically Consistent Latent Action Model for Vision-Language-Action Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-12T04:14:54.885244Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.10819"},"observation_digest":"sha256:bf6870f618e6d590d0b0bec613ad54479017c0740838e5b01ec734112fd2bc78","observation_id":"4b6f5c79-37d2-4272-af4f-69d874dc3b0e","resolution":{"observed_at":"2026-05-12T06:31:24.311493Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.10819","last_updated":"2026-05-13T09:16:02Z","snapshot_observed_at":"2026-08-04T23:42:58.419847Z","submitted_at":"2026-05-11T16:37:07Z","title":"ALAM: Algebraically Consistent Latent Action Model for Vision-Language-Action Models","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-14T21:14:56.501485Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.10819"},"observation_digest":"sha256:0fc5fe412245169f26ca9354c330d6efe00065f5930ce78cd8aa35b0b0d69cbe","observation_id":"3846c8cf-ba24-4056-bd2c-3f3460b8da1a","resolution":{"observed_at":"2026-05-14T21:17:59.512459Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.11832","last_updated":"2026-05-12T09:21:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-12T09:21:29Z","title":"Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-13T05:25:18.120832Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.11832"},"observation_digest":"sha256:e5caa84e07841b0776d209f9a8656d22cf4f08fc2698badc8c1f8ec370fe782f","observation_id":"0a8ecc01-d235-4f80-9c16-dbda403f7157","resolution":{"observed_at":"2026-05-13T05:27:18.555877Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.12090","last_updated":"2026-05-12T13:10:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-12T13:10:52Z","title":"World Action Models: The Next Frontier in Embodied AI","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-13T05:01:16.802019Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.12090"},"observation_digest":"sha256:744c8528160e78a408bc0e5ffa6d615083b09ad5303cf1957624ee65e87e6214","observation_id":"94eda5dc-5e1d-4375-b5d4-7d14f5e7616e","resolution":{"observed_at":"2026-05-13T05:07:18.222721Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.12334","last_updated":"2026-05-20T07:28:11Z","snapshot_observed_at":"2026-07-06T23:24:03.984179Z","submitted_at":"2026-05-12T16:16:15Z","title":"Reinforcing VLAs in Task-Agnostic World Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-13T04:17:51.349213Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.12334"},"observation_digest":"sha256:5f9c04a2713d35d2c151ca55e744c6d6f7559849d03b6dfd3f52be9dd61fb8dc","observation_id":"e350c569-99bb-40ab-a15e-6460dc5bb4c4","resolution":{"observed_at":"2026-05-13T04:27:14.346952Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.12334","last_updated":"2026-05-20T07:28:11Z","snapshot_observed_at":"2026-07-06T23:24:03.984179Z","submitted_at":"2026-05-12T16:16:15Z","title":"Reinforcing VLAs in Task-Agnostic World Models","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-21T08:13:40.975340Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.12334"},"observation_digest":"sha256:f048ffaf07675269878d3fa1da2b0224c4be7c5092d482361f76e1a234f8a5ff","observation_id":"83250fa3-dae4-452b-9f49-a028b296c522","resolution":{"observed_at":"2026-05-21T08:14:03.137453Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.17486","last_updated":"2026-05-17T14:55:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-17T14:55:32Z","title":"DyGRO-VLA: Cross-Task Scaling of Vision-Language-Action Models via Dynamic Grouped Residual Optimization","version":1},"reference_index":190,"source":"arxiv_source","source_observed_at":"2026-05-20T12:39:50.004269Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.17486"},"observation_digest":"sha256:cc86ff18dca9237f230f537f064ddf6d682a99abe58444b1ad5f4cd18c36e467","observation_id":"e536e61d-c586-4cd2-9aad-55f909d869e7","resolution":{"observed_at":"2026-05-20T12:43:17.190885Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2605.17912","last_updated":"2026-05-18T06:18:21Z","snapshot_observed_at":"2026-08-02T17:44:18.118027Z","submitted_at":"2026-05-18T06:18:21Z","title":"WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-20T10:59:54.879907Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2605.17912"},"observation_digest":"sha256:da038004196b396918cbc881bf08bf23bbc8cf4ca884be1eb5ec82fb7a932ddb","observation_id":"01949bb5-acef-458f-8bd7-702501e7251d","resolution":{"observed_at":"2026-05-20T11:03:13.598719Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2606.00113","last_updated":"2026-05-27T05:32:17Z","snapshot_observed_at":"2026-08-01T09:58:43.654749Z","submitted_at":"2026-05-27T05:32:17Z","title":"World Models for Robotic Manipulation: A Survey","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-06-29T12:24:18.025364Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2606.00113"},"observation_digest":"sha256:59ea4a9bfca75f54a087f4ee21d353e64ceafaf68429a54d3ba952ea51ecd7cd","observation_id":"fe759a5b-3562-459c-8262-e14b7ed8e015","resolution":{"observed_at":"2026-06-29T12:33:25.086511Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2606.09813","last_updated":"2026-06-08T17:55:41Z","snapshot_observed_at":"2026-08-04T14:42:13.332616Z","submitted_at":"2026-06-08T17:55:41Z","title":"iMaC: Translating Actions into Motion and Contact Images for Embodied World Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T16:16:31.703940Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2606.09813"},"observation_digest":"sha256:9d7aff1da16901f3a886470935111e867101e0826cd72df65a2d4ed5b226d0ae","observation_id":"f5372f02-a244-467a-8da8-82c7a1022c6f","resolution":{"observed_at":"2026-07-03T01:47:31.891774Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2606.12403","last_updated":"2026-06-10T17:59:08Z","snapshot_observed_at":"2026-08-01T17:35:24.729614Z","submitted_at":"2026-06-10T17:59:08Z","title":"World Pilot: Steering Vision-Language-Action Models with World-Action Priors","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-06-27T09:40:02.137152Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2606.12403"},"observation_digest":"sha256:9329cf20015ae64823dc8e9917865d95546763d038bb8710c3b1954ad67bb600","observation_id":"fefe26b1-47af-45cb-85ed-31a4a97f6ab1","resolution":{"observed_at":"2026-07-03T11:18:03.358870Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2606.15032","last_updated":"2026-06-28T03:48:42Z","snapshot_observed_at":"2026-07-06T23:52:28.557859Z","submitted_at":"2026-06-13T00:21:21Z","title":"How Should World Models Be Evaluated for Embodied Decision-Making? A Decision-Making-Centric Position","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-06-30T10:31:37.108792Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2606.15032"},"observation_digest":"sha256:dd6d41bba29fae5ddbd0b2ecb1c5cd33d85fa0297cd14e1dacfc0a577e9c824e","observation_id":"b85a1ac1-6acc-4769-9ef8-b27965d112bc","resolution":{"observed_at":"2026-06-30T10:34:36.498190Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2606.20698","last_updated":"2026-06-15T08:58:37Z","snapshot_observed_at":"2026-08-01T06:21:38.474874Z","submitted_at":"2026-06-15T08:58:37Z","title":"SafeDojo: Safe Reinforcement Learning for VLA via Interactive World Model","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-27T04:13:22.598591Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2606.20698"},"observation_digest":"sha256:e29325ba638bd6762768aa9d5d6d5daee1b7275b6028a977e9b6ddaa252e9b98","observation_id":"37a32824-084f-4ae0-9251-8509f1759774","resolution":{"observed_at":"2026-07-03T17:18:44.356532Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2606.32028","last_updated":"2026-07-02T02:48:47Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-06-30T17:54:32Z","title":"DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-01T04:54:53.250021Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2606.32028"},"observation_digest":"sha256:508a7c8323ac2b3de53c3f03f82f711ed6268a3d76c61bbc28ce74a34dd7fee2","observation_id":"f43df9bf-1190-4e02-a40f-8b410ea54780","resolution":{"observed_at":"2026-07-01T10:55:42.275069Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2606.32028","last_updated":"2026-07-02T02:48:47Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-06-30T17:54:32Z","title":"DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-03T21:54:30.642837Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2606.32028"},"observation_digest":"sha256:c04b8daea90770b7c2e32f972fa28f69b2ba98e9916cbb7c72db414d46ab4650","observation_id":"03cfdaba-45a9-48fa-85d1-6cbcc67ef2f2","resolution":{"observed_at":"2026-07-03T21:58:58.463141Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2607.02431","last_updated":"2026-07-02T17:00:37Z","snapshot_observed_at":"2026-07-07T00:07:52.110955Z","submitted_at":"2026-07-02T17:00:37Z","title":"WorldSample: Closed-loop Real-robot RL with World Modelling","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-03T10:57:40.128651Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2607.02431"},"observation_digest":"sha256:5d26831039a1fa3ed3f7327b35306a8dda814494a125e17efa8fb2951c6141b0","observation_id":"0be2ebab-9991-43c7-a4db-9cea96bb218c","resolution":{"observed_at":"2026-07-03T10:58:02.405856Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-12T06:41:57.276146Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02840","last_updated":"2026-07-03T00:23:30Z","snapshot_observed_at":"2026-08-05T03:55:15.314478Z","submitted_at":"2026-07-03T00:23:30Z","title":"TACO: TActile World Model as a Self-COrrector forScalable VLA Post-Training","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-12T06:41:57.276146Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2607.02840"},"observation_digest":"sha256:adff5d311ef23ed0d0111c822e0acafb4215fa91289d53964df599d88060fd5a","observation_id":"8bc31f8b-0971-4e50-b01f-c0085c241635","resolution":{"observed_at":"2026-07-12T06:41:57.276146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":"2509.24948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-07-10T08:36:59.803669Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","venue":"cs.RO","work_id":"e43fb37f-61a0-4911-b5e5-880083d7aa30","year":2025},"citing_paper":{"arxiv_id":"2607.08375","last_updated":"2026-07-09T11:49:57Z","snapshot_observed_at":"2026-08-01T14:34:54.273695Z","submitted_at":"2026-07-09T11:49:57Z","title":"WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-07-10T08:30:29.351159Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2607.08375"},"observation_digest":"sha256:8e32d8a62835f402c1c864e664b73107923a44c32afbaeef37c2c77b8371f10b","observation_id":"034631dc-3fd5-46d0-9294-3f70a4f7aa0d","resolution":{"observed_at":"2026-07-10T08:36:59.805192Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-08-01T00:52:27.635517Z","title":"World-env: Leveraging world model as a virtual environment for vla post-training.arXiv preprint arXiv:2509.24948,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.26037","last_updated":"2026-07-28T17:45:25Z","snapshot_observed_at":"2026-08-01T00:52:23.661967Z","submitted_at":"2026-07-28T17:45:25Z","title":"Wonder: Video World Model Done Better","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T00:52:27.635517Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2607.26037"},"observation_digest":"sha256:bb258d437f66d514196378e8c5a6b54dffeefcb732b411fe19c2f60d1d260a0d","observation_id":"c25b56c0-ccd4-49ee-a326-1339593967ae","resolution":{"observed_at":"2026-08-01T00:52:27.635517Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.24948","snapshot_observed_at":"2026-08-03T09:43:32.425225Z","title":"World-Env: Leveraging world model as a virtual environment for VLA post-training.arXiv preprint arXiv:2509.24948, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29302","last_updated":"2026-07-31T11:18:17Z","snapshot_observed_at":"2026-08-05T13:15:12.915208Z","submitted_at":"2026-07-31T11:18:17Z","title":"BWM: A Low-Cost High-Fidelity World Simulator for Robot Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T09:43:32.425225Z"},"links":{"cited_paper":"/paper/2509.24948","citing_paper":"/paper/2607.29302"},"observation_digest":"sha256:27c247631c8922a02ffd9f4003ead2f6319b4a642af27754c2d533eddfe5336c","observation_id":"5690d3ed-d876-470b-8fff-4147553cc1c2","resolution":{"observed_at":"2026-08-03T09:43:32.425225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2509.24948/citation-record","integrity":"/paper/2509.24948/integrity","json":"/paper/2509.24948/citation-record.json","paper":"/paper/2509.24948"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.14740","last_updated":"2024-02-26T18:26:25Z","snapshot_observed_at":"2026-07-06T17:34:07.737296Z","submitted_at":"2024-02-22T17:52:34Z","title":"Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs","version":2},"cited_work":{"arxiv_id":"2402.14740","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.14740","snapshot_observed_at":"2026-07-09T08:56:06.435604Z","title":"Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs","venue":"cs.LG","work_id":"7bb8f9ec-1241-4472-a4fa-c636c6d79892","year":2024},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2402.14740","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:f130d411202f2933e9913be888a814a4d18e7a3f9a8cd3ee3ce6102e92f65767","observation_id":"9339c109-9901-4ac2-aca9-fc16b18e7e73","resolution":{"observed_at":"2026-05-18T12:51:23.546120Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09985","last_updated":"2025-06-11T17:57:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-11T17:57:09Z","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","version":1},"cited_work":{"arxiv_id":"2506.09985","doi":"10.48550/arxiv.2506.09985","metadata_source":"pith","pith_arxiv_id":"2506.09985","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning","venue":"cs.AI","work_id":"a9c28401-f16a-4933-89f0-788e2f94e52b","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2506.09985","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:a05013adeec24e3e0a3f44bafb08c17211be6a8a90bbe7d79685935982f4b146","observation_id":"7d0e224a-43b3-4916-99fb-1379ff8754b7","resolution":{"observed_at":"2026-05-18T12:51:23.537135Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-03T19:08:37.559938+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-03T19:08:37.559938+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16609","last_updated":"2023-09-28T17:07:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-28T17:07:49Z","title":"Qwen Technical Report","version":1},"cited_work":{"arxiv_id":"2309.16609","doi":"10.48550/arxiv.2309.16609","metadata_source":"pith","pith_arxiv_id":"2309.16609","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen Technical Report","venue":"cs.CL","work_id":"bb1fd52f-6b2f-437c-9516-37bdf6eb9be8","year":2023},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2309.16609","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:cc08e1041a24941c925c91243aff64c8ec3f5767b03e9a2b4a804a40018a5e06","observation_id":"709af896-4e96-4d20-b238-97efbbb5bbdc","resolution":{"observed_at":"2026-05-18T12:51:23.561834Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-15T23:50:15.620681+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-15T23:50:15.620681+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24164","last_updated":"2026-01-08T17:01:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-31T17:22:30Z","title":"$\\pi_0$: A Vision-Language-Action Flow Model for General Robot Control","version":4},"cited_work":{"arxiv_id":"2410.24164","doi":"10.48550/arxiv.2410.24164","metadata_source":"pith","pith_arxiv_id":"2410.24164","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"$\\pi_0$: A Vision-Language-Action Flow Model for General Robot Control","venue":"cs.LG","work_id":"f790abdc-a796-482f-a40d-f8ee035ecfc2","year":2024},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2410.24164","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:d0421a5df7989a78320b7e2d93d46ba32667b29c1c97913b86b4e87da2d0f34d","observation_id":"88a4699e-ac36-4b88-b175-bdf47f50ee3d","resolution":{"observed_at":"2026-05-18T12:51:23.555450Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-25T22:28:38Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","version":1},"cited_work":{"arxiv_id":"2311.15127","doi":"10.48550/arxiv.2311.15127","metadata_source":"pith","pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","venue":"cs.CV","work_id":"4f68eada-27e3-437a-a2fe-6e4ca524d0d3","year":2023},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:a641f0d54065186057f8c1a854c939fb4b3e7352a7f571fd31519376544b2672","observation_id":"e54d6d5a-6128-45e4-bc90-617321a1110f","resolution":{"observed_at":"2026-05-18T12:51:23.551034Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-11T15:53:24.472993+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T15:53:24.472993+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.03645","last_updated":"2025-08-05T16:55:50Z","snapshot_observed_at":"2026-07-06T22:08:16.854644Z","submitted_at":"2025-08-05T16:55:50Z","title":"DiWA: Diffusion Policy Adaptation with World Models","version":1},"cited_work":{"arxiv_id":"2508.03645","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.03645","snapshot_observed_at":"2026-07-04T06:19:37.602235Z","title":"Diwa: Diffusion policy adaptation with world models.arXiv preprint arXiv:2508.03645","venue":null,"work_id":"3a794994-fc8d-42ab-83b5-03b8fe5ef610","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2508.03645","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:f66accd0a069036dc739779ab6624123a794efb04c780d4c238dd78593f4f649","observation_id":"0e2f8e2a-0fd3-4d05-8f46-cd7ebcb787fd","resolution":{"observed_at":"2026-05-18T12:51:23.541634Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.01600","last_updated":"2025-03-08T05:23:57Z","snapshot_observed_at":"2026-07-06T20:30:26.881629Z","submitted_at":"2025-02-03T18:35:42Z","title":"Reinforcement Learning for Long-Horizon Interactive LLM Agents","version":3},"cited_work":{"arxiv_id":"2502.01600","doi":"10.48550/arxiv.2502.01600","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.01600","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Reinforcement learning for long-horizon interactive llm agents","venue":"ArXiv.org","work_id":"7e929792-6a2a-42ff-a1db-763f890d8b4e","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2502.01600","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:1ed6fa08cf0563592ede9bbb995f05b758bf003a7c9268fb33be7dad7cf01934","observation_id":"0b5bd41e-3c99-44ec-a815-beaad8d3931f","resolution":{"observed_at":"2026-05-18T12:51:23.567751Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":"2010.11929","doi":"10.1175/jcli-d-22-0357.1","metadata_source":"pith","pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","venue":"cs.CV","work_id":"e96730e3-129b-4db6-b981-15ab7932e297","year":2020},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:a8ba3e094bc327127796010f8daedc30521c55d1f826b792e53ee24c50942d2e","observation_id":"d692c99c-0a00-4d60-82e3-9baf5b1a97cc","resolution":{"observed_at":"2026-05-18T12:51:23.507791Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2501.12948","doi":"10.1016/j.artmed.2024.103001","metadata_source":"pith","pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","venue":"cs.CL","work_id":"e6b75ad5-2877-4168-97c8-710407094d20","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:49be3cecfe1c37e3076db002a1683a555c943b8f6bd25b47c277d650f3013cce","observation_id":"16b59c80-6efc-44d0-b78a-97f47693ec61","resolution":{"observed_at":"2026-05-18T12:51:23.513586Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02193","last_updated":"2022-02-12T20:01:53Z","snapshot_observed_at":"2026-08-02T12:02:13.904371Z","submitted_at":"2020-10-05T17:52:14Z","title":"Mastering Atari with Discrete World Models","version":4},"cited_work":{"arxiv_id":"2010.02193","doi":"10.48550/arxiv.2010.02193","metadata_source":"pith","pith_arxiv_id":"2010.02193","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mastering Atari with Discrete World Models","venue":"cs.LG","work_id":"154f6f5f-bb34-456d-8107-45d5b51433ce","year":2020},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2010.02193","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:6a74bfc6eedb9d674b8f50463f1bab9648dded3d5e1e870fdb2f209fd2bcbbb3","observation_id":"1a755f0a-c73b-4890-8ce8-acbb321cbc23","resolution":{"observed_at":"2026-05-18T12:51:23.493368Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.06571","last_updated":"2025-08-15T05:19:30Z","snapshot_observed_at":"2026-08-01T16:27:10.848229Z","submitted_at":"2025-08-07T06:30:05Z","title":"IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model","version":3},"cited_work":{"arxiv_id":"2508.06571","doi":null,"metadata_source":"pith","pith_arxiv_id":"2508.06571","snapshot_observed_at":"2026-07-10T08:36:59.779636Z","title":"Irl-vla: Training an vision-language-action policy via reward world model","venue":"cs.AI","work_id":"949851a8-6409-4b4c-8066-025f27808795","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2508.06571","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:fb98d7d9fd503cbc739eb5672c3b9d68f00d871b663fecba2b64e440a1171171","observation_id":"0bf917a1-ce2c-4b1c-9be6-5d5b4f46a41b","resolution":{"observed_at":"2026-05-18T12:51:23.519299Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03744","last_updated":"2024-05-15T19:22:44Z","snapshot_observed_at":"2026-07-06T16:28:22.350574Z","submitted_at":"2023-10-05T17:59:56Z","title":"Improved Baselines with Visual Instruction Tuning","version":2},"cited_work":{"arxiv_id":"2310.03744","doi":"10.48550/arxiv.2310.03744","metadata_source":"pith","pith_arxiv_id":"2310.03744","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Improved Baselines with Visual Instruction Tuning","venue":"cs.CV","work_id":"5baeaa33-5986-44a3-85a4-fcabd6fc1e8d","year":2023},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2310.03744","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:541fda5cb5b183f03dbc0487a900c4a5cd0db9a3eab5458e40d2860080926242","observation_id":"892fc72e-fa05-42b6-925e-a9e40d79836a","resolution":{"observed_at":"2026-05-18T12:51:23.487852Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":"2304.07193","doi":"10.48550/arxiv.2304.07193","metadata_source":"pith","pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DINOv2: Learning Robust Visual Features without Supervision","venue":"cs.CV","work_id":"26b304e5-b54a-4f26-be7e-83299eca52e4","year":2023},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:b1adb3064afe62a93c656705cb8c5926e4c0d7566e74180ee11c227f39408468","observation_id":"8d181353-c753-4fc7-86e6-b7d7f83f3802","resolution":{"observed_at":"2026-05-18T12:51:23.532665Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.09747","last_updated":"2025-01-16T18:57:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-16T18:57:04Z","title":"FAST: Efficient Action Tokenization for Vision-Language-Action Models","version":1},"cited_work":{"arxiv_id":"2501.09747","doi":"10.48550/arxiv.2501.09747","metadata_source":"pith","pith_arxiv_id":"2501.09747","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"FAST: Efficient Action Tokenization for Vision-Language-Action Models","venue":"cs.RO","work_id":"83a8f966-6cfa-4f21-81f3-87440aae238f","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2501.09747","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:0171b2c005e9a466bf0317b2e6ad33dc868699a93d88339692eeda4d1aa172cd","observation_id":"193d796d-07f2-4d6b-aee5-002dfeeb6fd2","resolution":{"observed_at":"2026-05-18T12:51:23.523541Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":"1707.06347","doi":"10.1016/j.artint.2010.12.005","metadata_source":"pith","pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Proximal Policy Optimization Algorithms","venue":"cs.LG","work_id":"240c67fe-d14d-4520-91c1-38a4e272ca19","year":2017},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:8a123f9d267b55ed20d8784f970eed790885fdd8af5202575214233f177797f0","observation_id":"90216497-33a5-4286-b5a0-8dcff1a2a255","resolution":{"observed_at":"2026-05-18T12:51:23.502953Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17016","last_updated":"2025-05-22T17:59:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-22T17:59:45Z","title":"Interactive Post-Training for Vision-Language-Action Models","version":1},"cited_work":{"arxiv_id":"2505.17016","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.17016","snapshot_observed_at":"2026-07-04T20:50:12.325218Z","title":"Interactive Post-Training for Vision-Language-Action Models","venue":"cs.LG","work_id":"1ad0b2af-71bb-415b-b955-e3350f1a1ae8","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2505.17016","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:cf210428a8f95ec863c935c8ce3d31d92e730ae57af7fe0fd28fb840f0369f5b","observation_id":"835a556d-485d-4dac-9d28-64bcf6504dfc","resolution":{"observed_at":"2026-05-21T14:25:47.344448Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12213","last_updated":"2024-05-26T19:55:26Z","snapshot_observed_at":"2026-07-06T18:16:51.116432Z","submitted_at":"2024-05-20T17:57:01Z","title":"Octo: An Open-Source Generalist Robot Policy","version":2},"cited_work":{"arxiv_id":"2405.12213","doi":"10.48550/arxiv.2405.12213","metadata_source":"pith","pith_arxiv_id":"2405.12213","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Octo: An Open-Source Generalist Robot Policy","venue":"cs.RO","work_id":"f9ca0722-8855-48c3-a27a-0eefb7e19253","year":2024},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2405.12213","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:4a98c69baf165fd399b498e69b0fd72b8662e9460ce6eb417834ada92c11fed6","observation_id":"391b67e3-2e37-4c2c-84cf-bcaaefd7d91d","resolution":{"observed_at":"2026-05-18T12:51:23.528191Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":"2302.13971","doi":"10.48550/arxiv.2302.13971","metadata_source":"pith","pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LLaMA: Open and Efficient Foundation Language Models","venue":"cs.CL","work_id":"c018fc23-6f3f-4035-9d02-28a2173b2b9d","year":2023},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:a796ecb85535b8d59917b9d20f8c74801765222a4f8c92c2ed6e6857ced5ee94","observation_id":"5133c92a-0385-48c1-8aac-868ba565fc7a","resolution":{"observed_at":"2026-05-18T12:51:23.497922Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-01T11:08:05.851253+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-01T11:08:05.851253+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.06072","last_updated":"2025-03-26T08:33:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-12T11:47:11Z","title":"CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer","version":3},"cited_work":{"arxiv_id":"2408.06072","doi":"10.48550/arxiv.2408.06072","metadata_source":"pith","pith_arxiv_id":"2408.06072","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer","venue":"cs.CV","work_id":"f38fc088-12aa-4bf4-9ecd-08d3e797ccb7","year":2024},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"cited_paper":"/paper/2408.06072","citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:e26b07b6246b801a030f9ccc5d58e0f2a8819627ae4a225181ea742e3087c6d8","observation_id":"aa2d2470-dc8d-469f-8fff-fa12c7cf493b","resolution":{"observed_at":"2026-05-18T12:51:23.476018Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2020.298314","doi":"10.1109/access.2020.2983149","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Survey of Autonomous Driving: Common Practices and Emerging Technologies","venue":"IEEE Access","work_id":"8f6677c2-ebc3-4b02-b4a0-91cd7a305e41","year":2020},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:d6e421c2aa46c0cbb3839f827e5f9a4b0e47d651400fff8c3f249995610bcd41","observation_id":"1a9473d5-e214-47ed-a5de-786ffe777b96","resolution":{"observed_at":"2026-05-18T12:51:23.136173Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+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":"70d5034d-eb32-4088-a90c-5b05485dc967","year":2025},"citing_paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training","version":6},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-18T12:48:32.123998Z"},"links":{"citing_paper":"/paper/2509.24948"},"observation_digest":"sha256:eaad1428f1455dd07309b8dcdb246edf70719fb4c33c7e138cd68b1e6af3897b","observation_id":"3a231ac3-6172-4b80-a49c-8436e34c28df","resolution":{"observed_at":"2026-05-18T12:51:24.544937Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.24948","last_updated":"2026-04-27T05:41:00Z","latest_version":6,"primary_category":"cs.RO","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T15:45:19Z","title":"World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training"},"reference_resolution":{"displayed":21,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":1,"verified_exact":19,"verified_fuzzy":0},"total_outbound_references":21},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 31 inbound Pith citation observations for arXiv:2509.24948."}