{"as_of":"2026-08-09T12:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4826f056969a1684509f7fc0b97d111f87f8f00a63d58e444dbf1d1f5f7e3fb7","coverage":[{"denominator":59,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":59,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:47:50.172713Z","state":"measured"},{"denominator":63,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":63,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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":"2026-08-04T09:12:51.088632Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-10T06:26:27.481686Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.01546","snapshot_observed_at":"2026-08-04T09:12:51.088632Z","title":"Longdwm: Cross-granularity distil- lation for building a long-term driving world model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.16732","last_updated":"2026-06-25T19:54:02Z","snapshot_observed_at":"2026-08-07T10:54:05.573771Z","submitted_at":"2025-10-19T07:12:32Z","title":"A Comprehensive Survey on World Models for Embodied AI","version":3},"reference_index":188,"source":"pdf_text","source_observed_at":"2026-08-04T09:12:51.088632Z"},"links":{"cited_paper":"/paper/2506.01546","citing_paper":"/paper/2510.16732"},"observation_digest":"sha256:3f31427c6e8c5eb2933899f23e62fec96f5f0dddbc8fe21e9bec2c896776932c","observation_id":"3cd088f7-07b6-4aba-8155-ff5b73c71209","resolution":{"observed_at":"2026-08-04T09:12:51.088632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.01546","snapshot_observed_at":"2026-08-03T17:02:40.451968Z","title":"LongDWM: Cross-granularity distillation for building a long-term driving world model.arXiv preprint arXiv:2506.01546, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.10958","last_updated":"2026-06-01T17:54:44Z","snapshot_observed_at":"2026-08-03T18:19:00.778254Z","submitted_at":"2025-12-11T18:59:58Z","title":"WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World","version":2},"reference_index":104,"source":"pdf_text","source_observed_at":"2026-08-03T17:02:40.451968Z"},"links":{"cited_paper":"/paper/2506.01546","citing_paper":"/paper/2512.10958"},"observation_digest":"sha256:bed2570496ed534586c09266d049c9854b04a9f77b396acd4eec31df7e005311","observation_id":"420e0359-8b98-448d-93e6-fd24cf7d6f3f","resolution":{"observed_at":"2026-08-03T17:02:40.451968Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"cited_work":{"arxiv_id":"2506.01546","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.01546","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2506.01546 (2025) 3","venue":null,"work_id":"7596951c-4d3e-4388-8145-5393f56208d9","year":2025},"citing_paper":{"arxiv_id":"2604.17147","last_updated":"2026-04-18T21:00:26Z","snapshot_observed_at":"2026-07-06T23:04:19.063534Z","submitted_at":"2026-04-18T21:00:26Z","title":"ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-10T06:23:22.058330Z"},"links":{"cited_paper":"/paper/2506.01546","citing_paper":"/paper/2604.17147"},"observation_digest":"sha256:c6bb07c388bb4b7e1a28dd7e59c028304ee9a5e672105343c66591648550c4db","observation_id":"bf26ed9c-ebd7-4eb2-9fd1-e1e75653ebd1","resolution":{"observed_at":"2026-05-10T06:26:27.483110Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.01546","snapshot_observed_at":"2026-07-13T01:26:27.220907Z","title":"Longdwm: Cross-granularity distillation for building a long-term driving world model.arXiv preprint arXiv:2506.01546, 2025b","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.09655","last_updated":"2026-07-10T17:54:14Z","snapshot_observed_at":"2026-08-07T13:41:10.157141Z","submitted_at":"2026-07-10T17:54:14Z","title":"OpenLongTail: Generative Scaling of Long-Tail Driving Data","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-13T01:26:27.220907Z"},"links":{"cited_paper":"/paper/2506.01546","citing_paper":"/paper/2607.09655"},"observation_digest":"sha256:f1e6ee624ecbf2f21396f691044f643d40b586392b5e3f5f653e053ed59b755c","observation_id":"f92c35dd-22c3-4efa-b365-00ae323d9a11","resolution":{"observed_at":"2026-07-13T01:26:27.220907Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.01546/citation-record","integrity":"/paper/2506.01546/integrity","json":"/paper/2506.01546/citation-record.json","paper":"/paper/2506.01546"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1803.10122","last_updated":"2018-05-09T09:06:27Z","snapshot_observed_at":"2026-07-31T21:36:45.596575Z","submitted_at":"2018-03-27T15:08:55Z","title":"World Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.10122","snapshot_observed_at":"2026-08-07T11:46:58.980467Z","title":"World models.arXiv preprint arXiv:1803.10122, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.980467Z"},"links":{"cited_paper":"/paper/1803.10122","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:68b9721708fd0cdfae9e2e7bc3c0230bdc38a5ba47e4ea26cb8d48dd49a610fe","observation_id":"4a400a42-c8cb-4763-8778-83733654c949","resolution":{"observed_at":"2026-08-07T11:46:58.980467Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.297358Z","title":"A path towards autonomous machine intelligence version 0.9","venue":null,"work_id":"30398a75-19c2-449a-93f8-53a3aea2d70e","year":2022},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.004195Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:82adc0e1f81c5a1f82bb0aae9709492ba22bcde1e1ef397d87082a74732659ea","observation_id":"667ad5d2-34b7-45a1-8b9d-09a2a97bfe85","resolution":{"observed_at":"2026-08-07T11:48:04.307171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.01603","last_updated":"2020-03-17T17:10:58Z","snapshot_observed_at":"2026-08-09T02:21:17.479736Z","submitted_at":"2019-12-03T18:57:16Z","title":"Dream to Control: Learning Behaviors by Latent Imagination","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.01603","snapshot_observed_at":"2026-08-07T11:46:59.031775Z","title":"Dream to control: Learning behaviors by latent imagination.arXiv preprint arXiv:1912.01603, 2019","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.031775Z"},"links":{"cited_paper":"/paper/1912.01603","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:3af59b6277582c364fbfbd78337f55af9e87fc5636dcbf8425fb0d0b3d94005b","observation_id":"6e5df58c-8867-414a-a7bf-127a8f47f90a","resolution":{"observed_at":"2026-08-07T11:46:59.031775Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02193","snapshot_observed_at":"2026-08-07T11:46:59.069096Z","title":"Mastering atari with discrete world models.arXiv preprint arXiv:2010.02193, 2020","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.069096Z"},"links":{"cited_paper":"/paper/2010.02193","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:f6b907384c03bc695fa1a44730db8b71952f52028bfb9afdaa236c240c91f7db","observation_id":"e2f20f12-4f59-4009-a9f9-be48820a6009","resolution":{"observed_at":"2026-08-07T11:46:59.069096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.04104","snapshot_observed_at":"2026-08-07T11:46:59.113086Z","title":"Mastering diverse domains through world models.arXiv preprint arXiv:2301.04104, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.113086Z"},"links":{"cited_paper":"/paper/2301.04104","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:699daac4a959020ad6a658dcce0afb6ca16dfe69eda25321adf1a6754149c37e","observation_id":"35f31062-079c-41aa-b3e2-73cb92631b34","resolution":{"observed_at":"2026-08-07T11:46:59.113086Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.00568","last_updated":"2018-12-03T06:06:25Z","snapshot_observed_at":"2026-08-05T20:04:40.605065Z","submitted_at":"2018-12-03T06:06:25Z","title":"Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.00568","snapshot_observed_at":"2026-08-07T11:46:59.145898Z","title":"Visual foresight: Model-based deep reinforcement learning for vision-based robotic control.arXiv preprint arXiv:1812.00568, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.145898Z"},"links":{"cited_paper":"/paper/1812.00568","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:981a77293f5b002b33a6a738e810e743f6f213418adb5700da4bcb4fcf69f3ec","observation_id":"2661083e-36a0-44ac-9dda-f94985e1dd3f","resolution":{"observed_at":"2026-08-07T11:46:59.145898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.180265Z","title":"Carla: An open urban driving simulator","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.180265Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:01a18e2d58cf23069ce9299a11285695e2682379e5345670f8e8509264a0a48b","observation_id":"72df8b87-f52b-490a-9783-f3f1daabd8aa","resolution":{"observed_at":"2026-08-07T11:46:59.180265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.00690","last_updated":"2018-01-02T15:48:14Z","snapshot_observed_at":"2026-08-01T20:24:08.300098Z","submitted_at":"2018-01-02T15:48:14Z","title":"DeepMind Control Suite","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.00690","snapshot_observed_at":"2026-08-07T11:46:59.223222Z","title":"Deepmind control suite","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.223222Z"},"links":{"cited_paper":"/paper/1801.00690","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:b6528a5d1313772a3c7c59c34d9e571e42bb70abe868fde6a67f2c02d4568959","observation_id":"206a9620-d6d5-408f-9f2f-1fe6f85fa7b9","resolution":{"observed_at":"2026-08-07T11:46:59.223222Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17080","last_updated":"2023-09-29T09:20:37Z","snapshot_observed_at":"2026-07-06T16:25:21.571679Z","submitted_at":"2023-09-29T09:20:37Z","title":"GAIA-1: A Generative World Model for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17080","snapshot_observed_at":"2026-08-07T11:46:59.260528Z","title":"Gaia-1: A generative world model for autonomous driving","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.260528Z"},"links":{"cited_paper":"/paper/2309.17080","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:5be4bac99eeb4d0761a1083e696574a0c46dc338113e019ee92efff436c6500c","observation_id":"38e8555f-b215-4926-bc6d-1faec35ce97e","resolution":{"observed_at":"2026-08-07T11:46:59.260528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.09777","last_updated":"2023-11-27T05:09:29Z","snapshot_observed_at":"2026-07-06T16:19:57.322692Z","submitted_at":"2023-09-18T13:58:42Z","title":"DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.09777","snapshot_observed_at":"2026-08-07T11:46:59.294846Z","title":"Drivedreamer: Towards real-world-driven world models for autonomous driving.arXiv preprint arXiv:2309.09777, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.294846Z"},"links":{"cited_paper":"/paper/2309.09777","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:6a68fe94fe9e433286fff6359bbd38199661d6e0ad6c61cf037e0d7753b98757","observation_id":"9a7f9a72-f594-4e6a-a6e2-3e6e7f44912e","resolution":{"observed_at":"2026-08-07T11:46:59.294846Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17918","last_updated":"2023-11-29T18:59:47Z","snapshot_observed_at":"2026-07-06T16:54:33.882767Z","submitted_at":"2023-11-29T18:59:47Z","title":"Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17918","snapshot_observed_at":"2026-08-07T11:46:59.339105Z","title":"Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving.arXiv preprint arXiv:2311.17918, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.339105Z"},"links":{"cited_paper":"/paper/2311.17918","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:a41d02644e9a6398ca0082715e3d0fe431078a05fd1976630d65754fdac916c4","observation_id":"5db1b862-e40d-4a43-8d70-25241db47fe0","resolution":{"observed_at":"2026-08-07T11:46:59.339105Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.382275Z","title":"Vista: A generalizable driving world model with high fidelity and versatile controllability","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.382275Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:cbb9835153e04d37db1b927ea63616050d024a5ec6df61743851dc93544db090","observation_id":"262dda6a-1d24-44ec-a016-f4ba8098314e","resolution":{"observed_at":"2026-08-07T11:46:59.382275Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:48:04.025750Z","title":"Sora technical report","venue":null,"work_id":"a4bf19a9-2736-4c1c-9d18-cf4e3163f594","year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.417902Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:8cba16f3339508bd0c6b095bc98b816027e0314bfb0d528e2611e2ff0de42f45","observation_id":"c71186db-677f-4473-b182-7047880c81f1","resolution":{"observed_at":"2026-08-07T11:48:04.255464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03603","last_updated":"2025-03-11T08:14:25Z","snapshot_observed_at":"2026-08-03T00:44:01.942521Z","submitted_at":"2024-12-03T23:52:37Z","title":"HunyuanVideo: A Systematic Framework For Large Video Generative Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03603","snapshot_observed_at":"2026-08-07T11:46:59.453238Z","title":"Hunyuanvideo: A systematic framework for large video generative models.arXiv preprint arXiv:2412.03603, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.453238Z"},"links":{"cited_paper":"/paper/2412.03603","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:f03545000e278e0e7344ac425365135d86790b1dba4d41dc05d976aa8056f028","observation_id":"572766da-d16d-48a8-9c04-564eb04414dd","resolution":{"observed_at":"2026-08-07T11:46:59.453238Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.06072","snapshot_observed_at":"2026-08-07T11:46:59.487751Z","title":"Cogvideox: Text-to-video diffusion models with an expert transformer.arXiv preprint arXiv:2408.06072, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.487751Z"},"links":{"cited_paper":"/paper/2408.06072","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:20b70e6eb6fea6b10d6cab2aa0c6860e225d9d453e1a37c891b0a4de315ac718","observation_id":"f03e5416-4985-4c3a-9193-515248b4f1f6","resolution":{"observed_at":"2026-08-07T11:46:59.487751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.523598Z","title":"nuscenes: A multimodal dataset for autonomous driving","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.523598Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:69f9e63987cf3346bd5fb901e2404a751bc420c23b37408bb5b1bec5d8fef697","observation_id":"0591274a-a7a6-4698-8c4c-67247dc28ed7","resolution":{"observed_at":"2026-08-07T11:46:59.523598Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.558320Z","title":"Scalable diffusion models with transformers","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.558320Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:af81a41dde764bebd63475166115e35bc94f7bf6c4fe9489675a3adba851873d","observation_id":"c65f01ec-389a-4b34-a9b7-46ac7c3b2f9c","resolution":{"observed_at":"2026-08-07T11:46:59.558320Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.15894","last_updated":"2025-08-07T08:48:51Z","snapshot_observed_at":"2026-08-07T17:57:38.872776Z","submitted_at":"2025-02-21T19:28:05Z","title":"RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15894","snapshot_observed_at":"2026-08-07T11:46:59.603343Z","title":"Riflex: A free lunch for length extrapolation in video diffusion transformers.arXiv preprint arXiv:2502.15894, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.603343Z"},"links":{"cited_paper":"/paper/2502.15894","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:b2e7cc698811366c725149fc72a48029752e10fb0420a9929d6c5515cc20aece","observation_id":"eb12fa49-6f23-4817-bfb3-1f28b1900581","resolution":{"observed_at":"2026-08-07T11:46:59.603343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.649582Z","title":"Moviedreamer: Hierarchical generation for coherent long visual sequence","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.649582Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:0fa5ae82db98fa44150c9b828c0dd421f2ffbeebbbee22319823b4712a26a257","observation_id":"f4e5c9dd-d371-4bbf-aa40-a1f67644afa9","resolution":{"observed_at":"2026-08-07T11:46:59.649582Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.12346","last_updated":"2023-03-22T07:10:09Z","snapshot_observed_at":"2026-07-06T15:06:30.864553Z","submitted_at":"2023-03-22T07:10:09Z","title":"NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.12346","snapshot_observed_at":"2026-08-07T11:46:59.685586Z","title":"Nuwa-xl: Diffusion over diffusion for extremely long video generation.arXiv preprint arXiv:2303.12346, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.685586Z"},"links":{"cited_paper":"/paper/2303.12346","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:aba10d26265e756f82b5d7bf950bb24e3f783e384ec05aaf22b55076ff33cb33","observation_id":"c178382e-d639-4159-85ff-6a66ebcca95c","resolution":{"observed_at":"2026-08-07T11:46:59.685586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.718887Z","title":"High- resolution image synthesis with latent diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.718887Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:edc4cf5bea596823e9d60015b4dd5a623e108c2f3e4fac2c07f5216f1557f9b7","observation_id":"72dc8356-d93f-482e-9ee0-4de84188d6ab","resolution":{"observed_at":"2026-08-07T11:46:59.718887Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:59.771650Z","title":"Align your latents: High-resolution video synthesis with latent diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.771650Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:7e51d2983a3aa91c930cfd920193319b772416e5137c1308dc358920c49fc7ae","observation_id":"af7f9952-bc94-4946-b1f0-223a4306affb","resolution":{"observed_at":"2026-08-07T11:46:59.771650Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.04725","last_updated":"2024-02-08T18:08:57Z","snapshot_observed_at":"2026-07-06T15:52:13.602170Z","submitted_at":"2023-07-10T17:34:16Z","title":"AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.04725","snapshot_observed_at":"2026-08-07T11:46:59.816834Z","title":"Animatediff: Animate your personalized text-to-image diffusion models without specific tuning.arXiv preprint arXiv:2307.04725, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.816834Z"},"links":{"cited_paper":"/paper/2307.04725","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:a76e1195d6e16e065157dc9cac64418f8e818c52348391725448a1d580771e0a","observation_id":"ca61a6cb-8866-49dc-9559-61a6c6330d72","resolution":{"observed_at":"2026-08-07T11:46:59.816834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-08-07T21:47:08.589400Z","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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-07T11:46:59.862351Z","title":"Stable video diffusion: Scaling latent video diffusion models to large datasets.arXiv preprint arXiv:2311.15127, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.862351Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:a0ffb443a76d7b91b091f077cdf2af8c0001304ca68dbbef986022c66b8a5286","observation_id":"9b61f0f1-5a4f-4c2f-a8f8-fc1c130bdd69","resolution":{"observed_at":"2026-08-07T11:46:59.862351Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.04233","last_updated":"2024-05-07T11:52:49Z","snapshot_observed_at":"2026-08-09T05:07:43.521969Z","submitted_at":"2024-05-07T11:52:49Z","title":"Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.04233","snapshot_observed_at":"2026-08-07T11:46:59.897735Z","title":"Vidu: a highly consistent, dynamic and skilled text-to-video generator with diffusion models.arXiv preprint arXiv:2405.04233, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.897735Z"},"links":{"cited_paper":"/paper/2405.04233","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:1f7ea46a14c3411a1a93cb87c08e6a3a762af1f3de8c5df745e27984c4e6e389","observation_id":"5adca448-c3bb-461f-997c-2bfb5c6fbb01","resolution":{"observed_at":"2026-08-07T11:46:59.897735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:52.181674Z","title":"Nuwa-infinity: Autoregressive over autoregressive generation for infinite visual synthesis.Advances in Neural Information Processing Systems, 35:15420–15432, 2022","venue":null,"work_id":"393b7b58-c114-4b54-a45b-f924aaf8076b","year":2022},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.945219Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:fb63a958dd988d84e347fb5dd16bf6437c943e294b1f403eb79775fabe80d277","observation_id":"63fcdda7-734a-44ed-954a-62575f05908f","resolution":{"observed_at":"2026-08-07T11:47:52.212908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.14773","last_updated":"2025-04-16T13:38:58Z","snapshot_observed_at":"2026-08-06T14:42:35.046089Z","submitted_at":"2024-03-21T18:27:29Z","title":"StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.14773","snapshot_observed_at":"2026-08-07T11:46:59.981165Z","title":"Streamingt2v: Consistent, dynamic, and extendable long video generation from text.arXiv preprint arXiv:2403.14773, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:59.981165Z"},"links":{"cited_paper":"/paper/2403.14773","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:990de54e6849c66f144e5b251a92d5278dd7df2bb752401f85b1ec19ddbbac89","observation_id":"6459270e-51ee-4474-8542-3aacf5de1ab0","resolution":{"observed_at":"2026-08-07T11:46:59.981165Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.13549","last_updated":"2023-11-22T17:44:29Z","snapshot_observed_at":"2026-07-06T16:51:15.252642Z","submitted_at":"2023-11-22T17:44:29Z","title":"ADriver-I: A General World Model for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.13549","snapshot_observed_at":"2026-08-07T11:47:00.017376Z","title":"Adriver-i: A general world model for autonomous driving.arXiv preprint arXiv:2311.13549, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.017376Z"},"links":{"cited_paper":"/paper/2311.13549","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:e1c4a407c71e6ab8e1859d10d04045a0aa48d5145fea17a4ca55cf9ffe297ad6","observation_id":"eb4072ee-63d5-456c-998d-175c62ed402c","resolution":{"observed_at":"2026-08-07T11:47:00.017376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.18650","last_updated":"2025-05-24T11:35:09Z","snapshot_observed_at":"2026-08-07T14:25:57.955968Z","submitted_at":"2025-05-24T11:35:09Z","title":"ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.18650","snapshot_observed_at":"2026-08-07T11:47:00.052139Z","title":"Prophetdwm: A driving world model for rolling out future actions and videos.arXiv preprint arXiv:2505.18650, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.052139Z"},"links":{"cited_paper":"/paper/2505.18650","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:fdc0164834374f058c5070680bdbe0d0362e5890444379c66e49f9b278439c71","observation_id":"ef6585e4-e1d8-421c-99ff-842c66a39ef9","resolution":{"observed_at":"2026-08-07T11:47:00.052139Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02601","last_updated":"2024-05-03T04:50:27Z","snapshot_observed_at":"2026-08-06T19:21:54.069156Z","submitted_at":"2023-10-04T06:14:06Z","title":"MagicDrive: Street View Generation with Diverse 3D Geometry Control","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02601","snapshot_observed_at":"2026-08-07T11:47:00.094030Z","title":"Magicdrive: Street view generation with diverse 3d geometry control.arXiv preprint arXiv:2310.02601, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.094030Z"},"links":{"cited_paper":"/paper/2310.02601","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:559568c9af3b70a47d7be6815511ade86f155a1a73a46af92c2d86f1ac98d1eb","observation_id":"3c2884b7-b4ad-4d31-af54-5f45afcac20f","resolution":{"observed_at":"2026-08-07T11:47:00.094030Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:52.062046Z","title":"Occworld: Learning a 3d occupancy world model for autonomous driving","venue":null,"work_id":"2b11645c-e20f-4bfb-a7ba-12b061eb66a7","year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.130517Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:3bf0ff501477404e25a1fe1a0ee7f65e4d3ad487b9909b7b87fc5195e6d12e5c","observation_id":"4e83aba9-8ccd-495b-b019-96e31b54da03","resolution":{"observed_at":"2026-08-07T11:47:52.122447Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:00.165155Z","title":"Temporal triplane transformers as occupancy world models.arXiv preprint arXiv:2503.07338, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.165155Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:9f84c0776b05aa3b65836a549b6402efbcb91bf32961a724c836a73d62f4bdcf","observation_id":"bcbec392-857c-45cf-865d-7dbdf3e4b07e","resolution":{"observed_at":"2026-08-07T11:47:00.165155Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.09627","last_updated":"2024-12-12T18:59:59Z","snapshot_observed_at":"2026-08-05T03:34:06.291232Z","submitted_at":"2024-12-12T18:59:59Z","title":"Doe-1: Closed-Loop Autonomous Driving with Large World Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.09627","snapshot_observed_at":"2026-08-07T11:47:00.200689Z","title":"Doe-1: Closed-loop autonomous driving with large world model.arXiv preprint arXiv:2412.09627, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.200689Z"},"links":{"cited_paper":"/paper/2412.09627","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:5ec9a57c93d1ac75123cf545642539dae87d76744292b04344fb766507288321","observation_id":"3a925439-815a-4d93-b68e-de76a092771b","resolution":{"observed_at":"2026-08-07T11:47:00.200689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.01407","last_updated":"2024-12-03T13:14:39Z","snapshot_observed_at":"2026-07-06T20:00:09.775334Z","submitted_at":"2024-12-02T11:50:35Z","title":"HoloDrive: Holistic 2D-3D Multi-Modal Street Scene Generation for Autonomous Driving","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.01407","snapshot_observed_at":"2026-08-07T11:47:00.245613Z","title":"Holodrive: Holistic 2d-3d multi-modal street scene generation for autonomous driving.arXiv preprint arXiv:2412.01407, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.245613Z"},"links":{"cited_paper":"/paper/2412.01407","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:a582847b114b435ade1fd7e2af366d55afbac678a210ae23b68d86b8c00239f1","observation_id":"7aeffd4b-36ad-490b-ae0f-7214df40eafb","resolution":{"observed_at":"2026-08-07T11:47:00.245613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.13807","last_updated":"2025-07-25T02:30:46Z","snapshot_observed_at":"2026-08-08T02:56:46.319344Z","submitted_at":"2024-11-21T03:13:30Z","title":"MagicDrive-V2: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.13807","snapshot_observed_at":"2026-08-07T11:47:00.281052Z","title":"Magicdrivedit: High-resolution long video generation for autonomous driving with adaptive control.arXiv preprint arXiv:2411.13807, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.281052Z"},"links":{"cited_paper":"/paper/2411.13807","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:e967d82c232275e96b6c5214b2b557e8ca9ef4884106b4e8ab2951ab677ffac3","observation_id":"007e9952-2bf1-4772-bf7c-b500332258fe","resolution":{"observed_at":"2026-08-07T11:47:00.281052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.01595","last_updated":"2024-09-03T04:29:59Z","snapshot_observed_at":"2026-07-06T19:09:32.189008Z","submitted_at":"2024-09-03T04:29:59Z","title":"DiVE: DiT-based Video Generation with Enhanced Control","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.01595","snapshot_observed_at":"2026-08-07T11:47:00.324816Z","title":"Dive: Dit-based video generation with enhanced control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.324816Z"},"links":{"cited_paper":"/paper/2409.01595","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:2f37920d3ef9da337deb2e0950ab7cd9d0c3f4f7018438610fc014358e5900ea","observation_id":"02fcb41a-391c-4ce6-bb7f-b8c9cec9012a","resolution":{"observed_at":"2026-08-07T11:47:00.324816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.15208","last_updated":"2025-03-19T13:49:48Z","snapshot_observed_at":"2026-08-07T16:52:01.776398Z","submitted_at":"2025-03-19T13:49:48Z","title":"DiST-4D: Disentangled Spatiotemporal Diffusion with Metric Depth for 4D Driving Scene Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.15208","snapshot_observed_at":"2026-08-07T11:47:00.358770Z","title":"Dist-4d: Disentangled spatiotemporal diffusion with metric depth for 4d driving scene generation.arXiv preprint arXiv:2503.15208, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.358770Z"},"links":{"cited_paper":"/paper/2503.15208","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:10d0c695c10baaeae31fe661ceb805f09fef0d468b61c808fbc38a852b604529","observation_id":"adc644dc-6d24-46e9-b438-898f25b8336c","resolution":{"observed_at":"2026-08-07T11:47:00.358770Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05435","last_updated":"2025-03-11T12:38:27Z","snapshot_observed_at":"2026-07-06T20:03:06.933007Z","submitted_at":"2024-12-06T21:41:52Z","title":"UniScene: Unified Occupancy-centric Driving Scene Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05435","snapshot_observed_at":"2026-08-07T11:47:00.395079Z","title":"Uniscene: Unified occupancy-centric driving scene generation.arXiv preprint arXiv:2412.05435, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.395079Z"},"links":{"cited_paper":"/paper/2412.05435","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:b0ca1a7eb5c74bee075bc7cfb76398162cf35df26542a64408d8c8aa07066c51","observation_id":"005692a3-595a-4c1c-a42e-76386b3d6628","resolution":{"observed_at":"2026-08-07T11:47:00.395079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:00.438509Z","title":"Llava-next: A strong zero-shot video understanding model, April 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.438509Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:b13fdd0293d12d7a8f4d09deb730545d6894e8d0ae861b0ed7f907fcfc3409de","observation_id":"ce621a10-0bee-4d83-ba34-400b5821924f","resolution":{"observed_at":"2026-08-07T11:47:00.438509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:00.483953Z","title":"Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.483953Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:295610530e3f3155f5c7925ffeea8a544d2c1de1b2369d8b017e265159cfe31b","observation_id":"b8c04efd-ffff-4db0-a5c7-97488a70ea09","resolution":{"observed_at":"2026-08-07T11:47:00.483953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.963169Z","title":"Learning 3d photography videos via self-supervised diffusion on single images","venue":null,"work_id":"c81ac960-c9c8-44c7-8684-536f97c88679","year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.538906Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:2dfdb0e0c369135f84a53a875b16813ac6d32a77382c1f6dab5cbcfd5c2e4008","observation_id":"83a86584-f442-448f-af81-02981b6f85bb","resolution":{"observed_at":"2026-08-07T11:47:52.006400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.897195Z","title":"One-step diffusion with distribution matching distillation","venue":null,"work_id":"5f83f7f3-084a-4991-bba1-87ba2d9389dc","year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.583405Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:cd022c64d16d25fe983dadc105722a9eaf5422eaccbed3b0febce31a49099e99","observation_id":"7f779168-7ec7-49d2-9386-59f619d294b7","resolution":{"observed_at":"2026-08-07T11:47:51.919388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14867","last_updated":"2024-05-24T17:08:32Z","snapshot_observed_at":"2026-08-05T03:51:41.162350Z","submitted_at":"2024-05-23T17:59:49Z","title":"Improved Distribution Matching Distillation for Fast Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14867","snapshot_observed_at":"2026-08-07T11:47:00.618254Z","title":"Improved distribution matching distillation for fast image synthesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.618254Z"},"links":{"cited_paper":"/paper/2405.14867","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:c7865304d907f4126f330f6142d9045cd58d7004c161a62f01b8cf906e52d577","observation_id":"2d1fbaaa-5fd2-4a6d-8102-c4606583364d","resolution":{"observed_at":"2026-08-07T11:47:00.618254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:00.651537Z","title":"From slow bidirectional to fast causal video generators.arXiv preprint arXiv:2412.07772, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.651537Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:1442a6078c9a74b8ec3da9522e2e8d717afd935ef15949e2af54b941b7e4e432","observation_id":"fd3db0a8-f58e-49ca-b7b8-33dce26d642d","resolution":{"observed_at":"2026-08-07T11:47:00.651537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02101","last_updated":"2025-03-13T18:35:06Z","snapshot_observed_at":"2026-07-06T17:54:39.685251Z","submitted_at":"2024-04-02T16:52:41Z","title":"CameraCtrl: Enabling Camera Control for Text-to-Video Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02101","snapshot_observed_at":"2026-08-07T11:47:00.685250Z","title":"Cameractrl: Enabling camera control for text-to-video generation.arXiv preprint arXiv:2404.02101, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.685250Z"},"links":{"cited_paper":"/paper/2404.02101","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:0989a596984e95bd949127d6c105987ed96ed70f27dcf6f8774fae9c3a02fe17","observation_id":"3baeb08e-587f-41f5-aaa2-0c1bc40d61e2","resolution":{"observed_at":"2026-08-07T11:47:00.685250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.12781","last_updated":"2025-03-22T15:40:42Z","snapshot_observed_at":"2026-08-06T09:54:26.134418Z","submitted_at":"2024-07-17T17:59:05Z","title":"VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.12781","snapshot_observed_at":"2026-08-07T11:47:00.718882Z","title":"Vd3d: Taming large video diffusion transformers for 3d camera control.arXiv preprint arXiv:2407.12781, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.718882Z"},"links":{"cited_paper":"/paper/2407.12781","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:c99d2e918ca36fe01a7f4df030beeeeff0ba3b49371b951d1399a28f9ce2d8b2","observation_id":"bdbfa3f0-12a2-4962-8bd7-cb5a1b32900a","resolution":{"observed_at":"2026-08-07T11:47:00.718882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10126","last_updated":"2025-02-25T00:32:29Z","snapshot_observed_at":"2026-08-07T18:45:05.745904Z","submitted_at":"2024-06-14T15:33:00Z","title":"Training-free Camera Control for Video Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10126","snapshot_observed_at":"2026-08-07T11:47:00.763720Z","title":"Training-free camera control for video generation.arXiv preprint arXiv:2406.10126, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.763720Z"},"links":{"cited_paper":"/paper/2406.10126","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:6211a2564a2fb9586e626c8f0780e594f5feeeb07dcb8fb84cefbfc7c1d2d16e","observation_id":"51a552b4-2e8c-45a3-8c8e-f03fa6567f5c","resolution":{"observed_at":"2026-08-07T11:47:00.763720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02690","last_updated":"2025-01-05T23:55:33Z","snapshot_observed_at":"2026-08-06T14:33:47.079999Z","submitted_at":"2025-01-05T23:55:33Z","title":"GS-DiT: Advancing Video Generation with Pseudo 4D Gaussian Fields through Efficient Dense 3D Point Tracking","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02690","snapshot_observed_at":"2026-08-07T11:47:00.816915Z","title":"Gs-dit: Advancing video generation with pseudo 4d gaussian fields through efficient dense 3d point tracking.arXiv preprint arXiv:2501.02690, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:00.816915Z"},"links":{"cited_paper":"/paper/2501.02690","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:bb82b80ba0bfbd2b95d58656622aa5f9e5d9fd8fa415bb523b15480fe5aee2ae","observation_id":"bcb3a2dc-f5c6-4b1b-8e26-99e76102c154","resolution":{"observed_at":"2026-08-07T11:47:00.816915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:49.549503Z","title":"Drivegan: Towards a controllable high-quality neural simulation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.549503Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:8406104259f596f1e6922265e28519fd65ce071f002d2b07e00184a8a75afe12","observation_id":"3953cf5f-77ff-42a5-8524-be049147a8d7","resolution":{"observed_at":"2026-08-07T11:47:49.549503Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.816169Z","title":"Wovogen: World volume-aware diffusion for controllable multi-camera driving scene generation","venue":null,"work_id":"b8221c68-7d39-4a71-ad98-7deee5b521de","year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.640169Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:6878fa2af2190f94132a1c7fb439980b463f9411f4bcb34cf0bf8725a6403ea5","observation_id":"4ed420eb-de9f-4a15-9246-b9ab784b77b0","resolution":{"observed_at":"2026-08-07T11:47:51.837062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:49.692063Z","title":"Generalized predictive model for autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.692063Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:c2941794ae86f5a7a0c56fcd61a8db946ebae449e3ecc46b2887fd4e04c0e4f7","observation_id":"a09e1d22-a9c9-435b-b143-bbd08b3fc1aa","resolution":{"observed_at":"2026-08-07T11:47:49.692063Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04842","last_updated":"2025-03-06T14:40:15Z","snapshot_observed_at":"2026-07-06T20:02:39.525801Z","submitted_at":"2024-12-06T08:27:53Z","title":"UniMLVG: Unified Framework for Multi-view Long Video Generation with Comprehensive Control Capabilities for Autonomous Driving","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04842","snapshot_observed_at":"2026-08-07T11:47:49.751538Z","title":"Unimlvg: Unified framework for multi-view long video generation with comprehensive control capabilities for autonomous driving.arXiv preprint arXiv:2412.04842, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.751538Z"},"links":{"cited_paper":"/paper/2412.04842","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:fae5cdb824f506a9f783ec9e3a2499762080d8629199bd3cdd17e23e96a173b2","observation_id":"ae6a38c9-b824-4347-88a9-d7fdfbb12d6a","resolution":{"observed_at":"2026-08-07T11:47:49.751538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.687325Z","title":"Dynamicrafter: Animating open-domain images with video diffusion priors","venue":null,"work_id":"03fe6e4d-c2f0-4531-a9cd-5b716bd494b6","year":2025},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.810987Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:1605ceb010ae7eece70356bbf4102e1c54171aadd695b1da59ff888965436fad","observation_id":"79604640-358a-466b-8da1-42f6ef6efcfa","resolution":{"observed_at":"2026-08-07T11:47:51.766742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.04145","last_updated":"2023-11-07T17:16:06Z","snapshot_observed_at":"2026-08-02T12:25:34.488259Z","submitted_at":"2023-11-07T17:16:06Z","title":"I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.04145","snapshot_observed_at":"2026-08-07T11:47:49.885230Z","title":"I2vgen-xl: High-quality image-to-video synthesis via cascaded diffusion models.arXiv preprint arXiv:2311.04145, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.885230Z"},"links":{"cited_paper":"/paper/2311.04145","citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:b2e9458cfa70ef187c48222e159e05dcfd45a2ea24210c5bfb648e3e282161a9","observation_id":"0ef387e5-42b5-4bad-9192-7fffcdce9be6","resolution":{"observed_at":"2026-08-07T11:47:49.885230Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:49.940367Z","title":"Vbench: Comprehensive benchmark suite for video generative models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:49.940367Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:df0ea42dcab45e3d2be1f574620bac0ed9c4abc4b32e8c0db808cd30109530ab","observation_id":"dbd51a92-8c7a-4fc9-9837-16594c524ffd","resolution":{"observed_at":"2026-08-07T11:47:49.940367Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:50.011620Z","title":"Seine: Short-to-long video diffusion model for generative transition and prediction","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.011620Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:3bc578e10f4b17c19155dd4be442ffcaa95934449a40b3d306b7e6d1ccdf5c35","observation_id":"ec6931a9-5da1-4ddf-91ca-4e0100403e97","resolution":{"observed_at":"2026-08-07T11:47:50.011620Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.495343Z","title":"Framer: Interactive frame interpolation","venue":null,"work_id":"fdb67fd3-227e-4a9d-8aec-7c06af9b4430","year":null},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.069067Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:8ae0fdb9fbb2b14df654bbea9fdd7ce04b83cf686ba5eb5d67cf955ddc445d6a","observation_id":"29567794-8c8e-4222-a573-e33c0103bc65","resolution":{"observed_at":"2026-08-07T11:47:51.572889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.269332Z","title":"Navier-stokes, fluid dynamics, and image and video inpainting","venue":null,"work_id":"f639228d-9b7b-40d2-a38b-fc533b5089c1","year":2001},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.104111Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:91c97408c788055d53ffdaf6971b2f0a40a72dfa6b5e7b67981c87d6559fc04a","observation_id":"12b02a85-8d27-40b9-90ea-d338a9aca5ec","resolution":{"observed_at":"2026-08-07T11:47:51.387477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.090722Z","title":"Distillation.After obtaining the well-trained Coarse DiT and Fine DiT, we establish the distillation training","venue":null,"work_id":"0bf91f48-c7e3-429a-9024-c88063dbf1ba","year":null},"citing_paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T11:47:50.172713Z"},"links":{"citing_paper":"/paper/2506.01546"},"observation_digest":"sha256:5c3396fe1014eecca4d5edd285138b865678fb3d30ac79ab0a9a50a09e5b7b18","observation_id":"b9ef6034-e5fa-43cf-903f-ce737c2b9ca4","resolution":{"observed_at":"2026-08-07T11:47:51.170442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.01546","last_updated":"2025-06-02T11:19:23Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T10:49:37.282985Z","submitted_at":"2025-06-02T11:19:23Z","title":"LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model"},"reference_resolution":{"displayed":59,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":48,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":59},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 4 inbound Pith citation observations for arXiv:2506.01546."}