{"as_of":"2026-08-14T00:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6b4cccc71cc62a4ea7d5d97f97868bbd6f956dbee2fcd5a5bf4f47aa2cb91367","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:45:06.262282Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.12762/citation-record","integrity":"/paper/2507.12762/integrity","json":"/paper/2507.12762/citation-record.json","paper":"/paper/2507.12762"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:45:07.992304Z","title":"Autonomous vehicles: challenges, opportunities, and future implications for transportation policies","venue":null,"work_id":"6a355215-dc26-44c9-a7c7-a195a27ac447","year":2016},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:01.494439Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:f8390392c0a86fdf16996073bb565695fc725fd0926653a71c7b37ebb990ae03","observation_id":"0dc62768-4ef5-4800-b94e-af6e5260c3ce","resolution":{"observed_at":"2026-08-06T16:45:08.000742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.964986Z","title":"Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? Transportation Research Part A: Policy and Practice, 94:182–193, 2016","venue":null,"work_id":"ef39a45e-6aed-4600-bc09-0d02d8586e27","year":2016},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:01.609302Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:78b5a3cfbac4415ca7627bb66c3b4123a32b08cb02115859f710a1e9f79c95e7","observation_id":"3d1eeb15-90f6-407c-85fb-debee6240846","resolution":{"observed_at":"2026-08-06T16:45:07.973699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.939955Z","title":"Vision- based traffic accident detection and anticipation: A survey.IEEE Transactions on Circuits and Systems for Video Technology, 2023","venue":null,"work_id":"1defe13c-1225-476c-b02b-b995c79edad6","year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:01.737266Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:3ebdf0406784007b540a1665c0314aefb727169f3fd33785d7de5f34e9181403","observation_id":"896af7dd-ae95-4cb5-bf35-a2e9012b4166","resolution":{"observed_at":"2026-08-06T16:45:07.948645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.915427Z","title":"Dynamicattentionaugmentedgraphnetworkforvideoaccident anticipation","venue":null,"work_id":"6699b48d-d917-41f9-87b6-47af8e651bcc","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:01.869626Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:78c40c29e72f3b62cc43790cb2ffe06c2c11e23f00017927bfe478f306ccc381","observation_id":"126a94e9-064d-4c78-9766-29c080c8931e","resolution":{"observed_at":"2026-08-06T16:45:07.924057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.892821Z","title":"Antic- ipating accidents in dashcam videos","venue":null,"work_id":"003321d9-98fd-4f58-9b9a-b0a775ba1083","year":2016},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:01.995665Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:b49c498a90ebec4658f5fe2d95c4f13dabb8e061af81e9d64ea55de66694fc40","observation_id":"8efadc60-2229-4535-86e9-abaaf9b41270","resolution":{"observed_at":"2026-08-06T16:45:07.900035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.866614Z","title":"A dynamic spatial-temporal attention network for early anticipation of traffic accidents.IEEE Transactions on Intelligent Transportation Systems, 23(7):9590–9600, 2022","venue":null,"work_id":"6824bbba-d7ac-415f-8e70-aaf145a1548b","year":2022},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.129743Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:e757226560b3a19635fde69c08e88a979a55a2f3eb60cd6fa1ba1b822ddf4895","observation_id":"6bd849fe-3af0-4e16-9ac6-92b4e36df42f","resolution":{"observed_at":"2026-08-06T16:45:07.875292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.837881Z","title":"Spatiotemporal scene-graph embedding for autonomous vehicle collision prediction","venue":null,"work_id":"2e920f39-467e-4b03-9f17-2f711ff098b0","year":2022},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.277163Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:2c561352ae644d2c550e0c3a9e664344275170543b4350831ca56437372679b7","observation_id":"d5103560-4c84-4582-bfea-716eb560064f","resolution":{"observed_at":"2026-08-06T16:45:07.849960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.809523Z","title":"Global feature aggregation for accident anticipation","venue":null,"work_id":"3f634e3f-0a02-4514-91b1-84303642cdd9","year":2021},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.438231Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:0159da6733e99056dd9f2ccb4e92f8ac129d70ff57b17ed91c1c15fa3968212d","observation_id":"76ffa486-5768-4706-a7e5-06eda4ce4346","resolution":{"observed_at":"2026-08-06T16:45:07.820902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.778315Z","title":"Scene-graph augmented data-driven risk assessment of autonomous vehicle decisions","venue":null,"work_id":"ba5281bd-ca8a-4839-8fcb-1c41392d227d","year":2021},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.523843Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:3986d2d44ba42701b220ad9afe5d6fedcfcac6e863dea46bed016615395e0811","observation_id":"efd22c88-d6e3-4339-8597-68ccf2056034","resolution":{"observed_at":"2026-08-06T16:45:07.792056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.744347Z","title":"That-net: Two-layer hidden state aggregation based two-stream net- work for traffic accident prediction.Information Sciences, 634:744– 760, 2023","venue":null,"work_id":"8afe40fc-9e9f-4f5d-972d-f89a5ed87747","year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.635187Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:53656d6e89a8edd2d3f9a2773d2091f75ec269a73786721e400620e35ddd4de3","observation_id":"269ba8a9-5e97-4984-9856-b8684123daf8","resolution":{"observed_at":"2026-08-06T16:45:07.754501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.712427Z","title":"When, where, and what? a benchmark for accident anticipation and localization with large language models","venue":null,"work_id":"6c619b85-32eb-4d0e-b63f-a52c195b0f14","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.716374Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:075f383873cdded1d6134c677ff6da9b49ff1729dea854adbdc8b013604627f2","observation_id":"5464e5d1-cc6e-44e7-8d9d-78cbcf091689","resolution":{"observed_at":"2026-08-06T16:45:07.721160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.684923Z","title":"Review of graph-based hazardous event detection methods for autonomous driving systems","venue":null,"work_id":"e3bda10d-f552-49e5-96a4-df8464eea7a6","year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.838977Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:6257e1f639b75f1cfbfc426f879f0cb6873e8f38462654fbbdb70c795bf293a4","observation_id":"e0f6e932-4c18-40b8-8cee-f146f503e7ce","resolution":{"observed_at":"2026-08-06T16:45:07.695441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.664807Z","title":"Graph (graph): A nested graph-based framework for early accident antic- ipation","venue":null,"work_id":"c8c699c4-5852-4345-902f-537e91aa3a47","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:02.992566Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:6b8150413734761777665b162ea4ee2200ead3e493de1a1b6b18c6818f3b5688","observation_id":"c17d8cbc-8fba-4035-9a46-b4766b24c6e0","resolution":{"observed_at":"2026-08-06T16:45:07.671499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.638817Z","title":"Latte: A real-time lightweight attention-based traffic accident anticipation engine","venue":null,"work_id":"30267c28-a5d5-4676-9600-8da3d5b008c3","year":2025},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.156894Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:d3c59c4e26a89a1e2140fc82948a326742f21c8a727048e3b35f6c2e6851153a","observation_id":"b5d9f9f7-1de7-4eec-8b8f-fe6b0ba4359a","resolution":{"observed_at":"2026-08-06T16:45:07.646973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.613377Z","title":"Crash: Crash recognition and anticipation system harnessing with context-aware and temporal focus attentions","venue":null,"work_id":"e05cd5d4-0628-46d8-a4ce-e16f3752d73c","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.308474Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:ef4b13d26bf8bda99b18304d93891aad16d37c3321769ab3ba9b9afc3069003e","observation_id":"aa7fcaf6-85cb-47a5-859f-10f785c893f1","resolution":{"observed_at":"2026-08-06T16:45:07.620676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.567928Z","title":"Real-time acci- dent anticipation for autonomous driving through monocular depth- enhanced3dmodeling","venue":null,"work_id":"2b18db24-6612-421e-8a2b-cfd3ec6cde41","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.460963Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:caf523829c61f00511304541027c4a946eba7227d138fad671410ff7e69001ec","observation_id":"3555c7c5-fc81-4d7a-b819-eadc97cc8dad","resolution":{"observed_at":"2026-08-06T16:45:07.598137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.17705","last_updated":"2024-11-05T18:02:53Z","snapshot_observed_at":"2026-08-12T23:56:41.126523Z","submitted_at":"2024-05-27T23:38:10Z","title":"DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.17705","snapshot_observed_at":"2026-08-06T16:45:03.608314Z","title":"Dc-gaussian: Improving3dgaussiansplattingforreflectivedashcamvideos","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.608314Z"},"links":{"cited_paper":"/paper/2405.17705","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:d1b5b6d1324f51b8511d818b7643b8ad9ee67c2134730dee15555fa6a657f524","observation_id":"b5addd15-aab3-4bf5-befa-7cc2043c0e93","resolution":{"observed_at":"2026-08-06T16:45:03.608314Z","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":"2026-08-06T16:45:07.537932Z","title":"Reflection removal under fast forward camera motion.IEEE Transactions on Image Processing, 26(12):6061–6073, 2017","venue":null,"work_id":"04187a12-87db-4721-8e45-c818d77bc11d","year":2017},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.682650Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:8b7d72a4e6009a6dea9e19a129cbcabf10ed2ef28b2ca8068ba24b668b8ee1f8","observation_id":"18004550-c867-424e-bcb4-71fafbb5d985","resolution":{"observed_at":"2026-08-06T16:45:07.547129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.500969Z","title":"Real-time automatic traffic accident recognition using hfg","venue":null,"work_id":"832fb916-a3a4-4f1c-a283-7a2d05126c19","year":2010},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.718762Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:c9b5f2fa49923a45ae3362746ce65ee87692d05fed76fb4db9f1d3f2beb3eb9f","observation_id":"3c57e919-6f75-467a-b120-8ca8e891d11a","resolution":{"observed_at":"2026-08-06T16:45:07.511850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.468351Z","title":"Unsupervisedtrafficaccidentdetectioninfirst-personvideos","venue":null,"work_id":"18e55317-85a6-4630-bce6-70721635b86c","year":2019},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.824035Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:f3f725a162aca386748a1a6cd2f7523b5b0e35e3f367c1d045489b44e8bd4dde","observation_id":"577bdb2a-8951-48e8-8f89-70ebc0b20490","resolution":{"observed_at":"2026-08-06T16:45:07.478134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.267898Z","title":"IEEE Transactions on Intelligent Vehicles, 9(1):2249–2261, 2023","venue":null,"work_id":"63a63342-435c-46d1-a9a4-7e0541985af0","year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:03.987777Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:15e8e1fa00b3e6207a32af92f6ce62246a536f6c06c826b2f9df82f0c9455ca7","observation_id":"a25b94ba-87cc-4938-a6f0-cd652deae5f7","resolution":{"observed_at":"2026-08-06T16:45:07.276285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.240465Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding","venue":null,"work_id":"17792caf-88f2-458a-98c1-5ee82ac11b0a","year":2019},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:04.130405Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:0e6ee3679f123289b3a183466f4b75d58e4ff36eba06e04f8bbdc95029b283fa","observation_id":"c6984d43-5320-4e9a-b737-af75c23bdd9e","resolution":{"observed_at":"2026-08-06T16:45:07.247518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.211410Z","title":"Vision- language models for vision tasks: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024","venue":null,"work_id":"a447795c-ea4d-4ce4-a8f3-25a3a741d04d","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:04.357709Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:78b5265781cc2327e5be743dd840a16d7a7e9103ea6b25e6975f8698d9c78377","observation_id":"f68bd6a6-c0b7-4645-a2da-bc5ffe0fff4e","resolution":{"observed_at":"2026-08-06T16:45:07.219040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:04.523816Z","title":"Learning transferable visual mod- elsfromnaturallanguagesupervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:04.523816Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:d6e21c766697897608b88d26e2b364c9c2dcb1ff35854e7cfe4bf2e42476fe51","observation_id":"1cd6484d-d2ef-48f8-a2ae-3c6fa853b44c","resolution":{"observed_at":"2026-08-06T16:45:04.523816Z","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":"2026-08-06T16:45:07.164375Z","title":"Sun database: Large-scale scene recognition from abbeytozoo","venue":null,"work_id":"194fb66d-1d3d-4985-999c-c378982317c9","year":2010},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:04.712458Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:38a8338e878065339729d10f8024f97efda72b5d337ea9b59ca3ad909e888bd2","observation_id":"c06af918-e24e-4f23-abe6-0c484e334f18","resolution":{"observed_at":"2026-08-06T16:45:07.171057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.137158Z","title":"Enhancing vision-language models with scene graphs for traffic accident understanding","venue":null,"work_id":"12b3b921-adf3-4be6-b00a-71cd5ca16471","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:04.890842Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:e37be18b6088c8b34443316d124baa7744ae7e85ad231997c869db68cfdc7b0b","observation_id":"bc243f94-0646-4352-a831-4e1dd006cccc","resolution":{"observed_at":"2026-08-06T16:45:07.144391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.117458Z","title":"Cross-domain traffic scene understanding by integrating deep learn- ing and topic model.Computational intelligence and neuroscience, 2022(1):8884669, 2022","venue":null,"work_id":"c112db86-9eb3-4e88-8ce9-0cc568d83f72","year":2022},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:05.063725Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:2b93d7ea6b0ba827c4d1723c6a0e69be460efda47bbb6635299d797ab7b86bbd","observation_id":"d44f8ec8-5efb-433c-bc26-579991118fc9","resolution":{"observed_at":"2026-08-06T16:45:07.122935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.099894Z","title":"World models for autonomous driving: An initial survey.IEEE Transactions on Intelligent Vehicles, 2024","venue":null,"work_id":"02d2f85e-812b-4bcb-869b-6d28ee588a4e","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:05.229944Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:6d60ff4ae887d1570e53916c2f2591aebfb2b02ddca2bbfb86bb0840d6194633","observation_id":"47053044-4ad4-4841-adfb-2c3c0814e4c1","resolution":{"observed_at":"2026-08-06T16:45:07.105290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-06T16:45:05.420535Z","title":"Gaia-1: A generative world model for autonomous driving.arXiv preprint arXiv:2309.17080, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:05.420535Z"},"links":{"cited_paper":"/paper/2309.17080","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:06ddd609f28a5051eba9d110fc7590a467079a6b619ee0195a94e0071c50e751","observation_id":"34f9a795-c51a-45a9-8020-ace42ac7d2d4","resolution":{"observed_at":"2026-08-06T16:45:05.420535Z","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":"2026-08-06T16:45:07.074721Z","title":"Driving into the future: Multiview visual fore- casting and planning with world model for autonomous driving","venue":null,"work_id":"f1f9c18b-0354-45e5-a40d-818e0399e54a","year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:05.580335Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:671220cd6ae97268ee21531912b423cce963cf8f04d46337ade32ccd38cdc645","observation_id":"78502dd1-739f-46c8-ae10-8f26628bc66d","resolution":{"observed_at":"2026-08-06T16:45:07.083181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.17398","last_updated":"2024-10-28T05:53:17Z","snapshot_observed_at":"2026-08-13T03:00:17.299004Z","submitted_at":"2024-05-27T17:49:15Z","title":"Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.17398","snapshot_observed_at":"2026-08-06T16:45:05.769443Z","title":"Vista:Ageneralizable driving world model with high fidelity and versatile controllability","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:05.769443Z"},"links":{"cited_paper":"/paper/2405.17398","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:8a19c074a0af1ba1ba3cfde311f1e5b4950480776db1eab1179cf5cce103b15b","observation_id":"cb935754-98bb-4210-af1e-dce71b325508","resolution":{"observed_at":"2026-08-06T16:45:05.769443Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17177","last_updated":"2024-04-17T18:41:39Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-27T03:30:58Z","title":"Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17177","snapshot_observed_at":"2026-08-06T16:45:05.944449Z","title":"Sora: A review on background, technology, limitations, and opportunities of large vision models.arXiv preprint arXiv:2402.17177, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:05.944449Z"},"links":{"cited_paper":"/paper/2402.17177","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:5dd50d7c7f2b5b8aae6b8fdcd36607fcec699d2d303f14ca5157f2ecee6d2e24","observation_id":"83fb52bd-b8c9-4764-adad-922f06a9abcb","resolution":{"observed_at":"2026-08-06T16:45:05.944449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00415","last_updated":"2024-08-01T09:32:01Z","snapshot_observed_at":"2026-08-12T23:10:23.734881Z","submitted_at":"2024-08-01T09:32:01Z","title":"DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00415","snapshot_observed_at":"2026-08-06T16:45:06.101252Z","title":"Drivearena: A closed-loop generative simulation platform for autonomous driving.arXiv preprint arXiv:2408.00415, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.101252Z"},"links":{"cited_paper":"/paper/2408.00415","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:59cbc86a0eabe057fa847eb5584cc292d08c39b8261bcc063fd6a5a0ad8c8a2a","observation_id":"5dce0c73-439b-4a66-9d31-69e362b70445","resolution":{"observed_at":"2026-08-06T16:45:06.101252Z","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":"2026-08-06T16:45:07.056094Z","title":"Recurrentworldmodelsfacilitate policyevolution","venue":null,"work_id":"9ce7739b-9555-4ac2-8c58-0fc5eec215ea","year":2018},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.118211Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:480226957e5fd6c4289aa3309814b183edb815971d21f763a589e333a13c0324","observation_id":"f254a01f-a9d8-4430-bd22-f34e135e9dd3","resolution":{"observed_at":"2026-08-06T16:45:07.061495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02193","snapshot_observed_at":"2026-08-06T16:45:06.129037Z","title":"Mastering atari with discrete world models","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.129037Z"},"links":{"cited_paper":"/paper/2010.02193","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:0adcaf871b3450e43b95d5cadd7b672b25980eaddc9c8d02315efb2c8dbe3fe5","observation_id":"0a439c4f-0eb5-40cd-b1a9-591d9997b720","resolution":{"observed_at":"2026-08-06T16:45:06.129037Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.10122","last_updated":"2024-10-01T12:07:31Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-16T10:59:44Z","title":"Video-LLaVA: Learning United Visual Representation by Alignment Before Projection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.10122","snapshot_observed_at":"2026-08-06T16:45:06.134462Z","title":"Video-llava: Learning united visual representation by alignmentbeforeprojection","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.134462Z"},"links":{"cited_paper":"/paper/2311.10122","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:b8317d5206dfd65d743681079235c59c7ba18dcaf291375996e0de17ec7dd794","observation_id":"916b8675-d1e5-4ab7-89e7-9915a5bfeaec","resolution":{"observed_at":"2026-08-06T16:45:06.134462Z","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":"2026-08-06T16:45:07.038729Z","title":"Openstreetmap: User- generatedstreetmaps","venue":null,"work_id":"57c45879-cb54-439e-bbdf-c62391c61260","year":2008},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.140035Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:ca4c6eb3b44ebad8eb90ce02bc3405867ccffc221f4f9546e69cc632d3f65fe0","observation_id":"a4592372-be5d-4b25-96b5-1382302a2ab4","resolution":{"observed_at":"2026-08-06T16:45:07.044507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:07.017099Z","title":"Recent development and applications of sumo-simulation of urban mobility","venue":null,"work_id":"2c82077c-9f0c-4151-b94c-81159f6359c5","year":2012},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.144904Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:73a842c650adc43a1c751b41798bf2d29df5604ab7436b09a06a590c82a6e3f4","observation_id":"3ccbdf2d-0154-4462-bb2d-7dc09d945992","resolution":{"observed_at":"2026-08-06T16:45:07.023593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.992342Z","title":"Planning-oriented autonomous driving","venue":null,"work_id":"c8d0b739-b584-4898-b36a-66c9b468f68f","year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.151611Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:4e16a56f29c01efe3f5d3fadc6ea94ede2c49b3a3f5057a41284d482e81ced95","observation_id":"bb60698c-619d-4876-9a02-d982ed4fa9df","resolution":{"observed_at":"2026-08-06T16:45:07.001727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.959205Z","title":"nuscenes: A multimodal dataset for autonomousdriving","venue":null,"work_id":"d8caca42-a43c-4f03-acea-df871770c120","year":2020},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.157540Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:2e122d82b0c0d14a5c05c867e0e8933b4565ec71913deb7dd877c717de00e93d","observation_id":"9fe8f151-b643-45cc-8878-190e5f2e7440","resolution":{"observed_at":"2026-08-06T16:45:06.975409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.936674Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"4aa69f3e-2d5d-4778-8f0b-dc3e0320b339","year":2022},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.162433Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:25f74fbb37bcfcfa93a0bdfcd13a7e6574d0d2727de367dcd4bc732add92e5ce","observation_id":"f955ef42-576d-48e6-a867-2d9c27fc32d2","resolution":{"observed_at":"2026-08-06T16:45:06.943371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.09985","last_updated":"2024-01-18T14:01:20Z","snapshot_observed_at":"2026-08-13T04:39:52.378951Z","submitted_at":"2024-01-18T14:01:20Z","title":"WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.09985","snapshot_observed_at":"2026-08-06T16:45:06.168043Z","title":"Worlddreamer: Towards general world models for video generation via predicting masked tokens.arXiv preprint arXiv:2401.09985, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.168043Z"},"links":{"cited_paper":"/paper/2401.09985","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:f6d7b5f892234e70f18f833ce2d583f6df977b9abfd6808881e461515fabc9e6","observation_id":"5a0906ad-ae6e-45c4-98de-e213bc1142c3","resolution":{"observed_at":"2026-08-06T16:45:06.168043Z","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":"2026-08-06T16:45:06.916560Z","title":"Fvd: A new metric for video generation","venue":null,"work_id":"5a3df6ad-77a9-44e5-aad7-dabe6ae7c92b","year":null},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.173825Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:6182d492ad4bacf0e720faf4b6e9a315d2ca36e30e35bd181bc4b7c1f61301bc","observation_id":"9c295ebb-757a-4210-8e5c-4102c0ed4139","resolution":{"observed_at":"2026-08-06T16:45:06.923016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.886485Z","title":"Frechetinceptiondistance(fid) for evaluating gans.China University of Mining Technology Beijing Graduate School, 3(11), 2021","venue":null,"work_id":"1457d6bd-8a14-4114-8dbb-4eb21c6ddd9c","year":2021},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.179014Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:4f555652a4a6f650c989e63737944fd7a378a7ca912f1ec28af23b0337006522","observation_id":"8cdc0715-ff9d-4dc5-9e1b-732ec334c070","resolution":{"observed_at":"2026-08-06T16:45:06.893289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.06137","last_updated":"2022-12-12T18:59:58Z","snapshot_observed_at":"2026-08-13T13:23:18.177173Z","submitted_at":"2022-12-12T18:59:58Z","title":"NMS Strikes Back","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.06137","snapshot_observed_at":"2026-08-06T16:45:06.183922Z","title":"Nms strikes back","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.183922Z"},"links":{"cited_paper":"/paper/2212.06137","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:0b4dfdf7853c0b739172b2a7bb922e3951b93640808bbf564432f2675a549cab","observation_id":"29769738-58bc-49ef-8cac-17a2ec0cc649","resolution":{"observed_at":"2026-08-06T16:45:06.183922Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-12T14:19:29.389332Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-06T16:45:06.188820Z","title":"Very deep convolu- tional networks for large-scale image recognition","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.188820Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:1d3aacc1818190d51a44098e6465ba8d2cdbce0037a0097ea224978c26881dd2","observation_id":"808eef8b-efcb-47fb-b066-acab1729db91","resolution":{"observed_at":"2026-08-06T16:45:06.188820Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12288","last_updated":"2023-02-23T19:13:10Z","snapshot_observed_at":"2026-07-06T14:55:15.719380Z","submitted_at":"2023-02-23T19:13:10Z","title":"ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12288","snapshot_observed_at":"2026-08-06T16:45:06.194055Z","title":"Zoedepth: Zero-shot transfer by combining relative and metric depth.arXiv preprint arXiv:2302.12288, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.194055Z"},"links":{"cited_paper":"/paper/2302.12288","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:2b341c464e4504eeb82ba28c1e9ada0a9c4fb9357b99d52906a1c9db48f7bbc5","observation_id":"5e1313e8-5a9e-44bb-822c-8515d501145d","resolution":{"observed_at":"2026-08-06T16:45:06.194055Z","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":"2026-08-06T16:45:06.865395Z","title":"InProceedings of the IEEE conference on computer vision and pattern recognition, pages 3061–3070, 2015","venue":null,"work_id":"b4ad59f0-0dc5-4338-b737-8626d57ca073","year":2015},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.199471Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:576b929990cdc76f36aeb8a9ec66149d053fdb6b515932b4b01871d2aaed8b90","observation_id":"3bbaf938-8b7a-4b30-9754-0a23b55bd41e","resolution":{"observed_at":"2026-08-06T16:45:06.872247Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.842832Z","title":"Long short-term memory.Neural Computation MIT- Press, 1997","venue":null,"work_id":"4b7c06b2-5e5e-47be-b240-c94d28b434d0","year":1997},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.205519Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:46caa12965c182dc3bedd53f41717b8c3918a2da13cef5bb1e67f27bcf68d274","observation_id":"e8b99a8d-edd5-4674-aab3-29f51b4b7385","resolution":{"observed_at":"2026-08-06T16:45:06.849649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.3555","last_updated":"2014-12-11T06:46:53Z","snapshot_observed_at":"2026-08-13T10:35:27.214652Z","submitted_at":"2014-12-11T06:46:53Z","title":"Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.3555","snapshot_observed_at":"2026-08-06T16:45:06.210131Z","title":"Empirical evaluation of gated recurrent neural networks on sequence modeling.arXiv preprint arXiv:1412.3555, 2014","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.210131Z"},"links":{"cited_paper":"/paper/1412.3555","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:9cd02039851c77a9ff17187e33d35fb3c7d3ad5803a4e64ae32da186de44b73d","observation_id":"e0c72947-23c9-40e8-b39f-9f0fd12be8d2","resolution":{"observed_at":"2026-08-06T16:45:06.210131Z","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":"2026-08-06T16:45:06.819648Z","title":"Temporal convolutional networks for action segmen- tation and detection","venue":null,"work_id":"85bddee4-5d4c-4d91-a049-f932598796e9","year":2017},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.214884Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:33c1b374e40aa7c80ec777a69d46bf6abc093357d909f2ccb70a8561b20c78ac","observation_id":"16b08676-5239-48cf-aad2-3eaa7fdbda5f","resolution":{"observed_at":"2026-08-06T16:45:06.826306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.07122","last_updated":"2016-04-30T18:19:37Z","snapshot_observed_at":"2026-07-06T04:37:24.552839Z","submitted_at":"2015-11-23T07:32:14Z","title":"Multi-Scale Context Aggregation by Dilated Convolutions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.07122","snapshot_observed_at":"2026-08-06T16:45:06.219714Z","title":"Multi-scalecontextaggregationbydilatedconvolutions","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.219714Z"},"links":{"cited_paper":"/paper/1511.07122","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:23e629b75a22c6b801dd179e33a26f5883b52b04f2c2b93a94442ef3fbdcdb33","observation_id":"8355cdaa-e90c-4651-b367-ae035c133ffe","resolution":{"observed_at":"2026-08-06T16:45:06.219714Z","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":"2026-08-06T16:45:06.793753Z","title":"IEEEtransactionsonpatternanalysisandmachine intelligence, 45(1):444–459, 2022","venue":null,"work_id":"c6f61bdb-d6de-498f-a60e-c399a65d51c3","year":2022},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.225821Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:d3ef673cdefb7b6d7306b850826aac8cb10eae5783f4879c505b678a06e397e0","observation_id":"a08b9b57-0e0d-4940-86b5-e3ad952d79df","resolution":{"observed_at":"2026-08-06T16:45:06.801757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.230694Z","title":"Bdd100k: A diverse driving dataset for heterogeneous multitask learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.230694Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:d46a0d38aefb83a30e0ecd07890a2510a09729289abbce8bd33f115c4576de47","observation_id":"38917848-a6b1-48e6-9f02-70f082ce9ef5","resolution":{"observed_at":"2026-08-06T16:45:06.230694Z","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":"2026-08-06T16:45:06.751635Z","title":"Uncertainty-basedtrafficaccident anticipation with spatio-temporal relational learning","venue":null,"work_id":"500184d7-28a0-4405-92db-a5c67090f607","year":2020},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.236771Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:1df1caf8b79e0a91b825ffbd627d4d32c9c330fef9c4d70aa9337a2b103b75f2","observation_id":"9b6ede26-8a2f-4f9a-9c97-d539306b3cc1","resolution":{"observed_at":"2026-08-06T16:45:06.759278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.722781Z","title":"A review onthelongshort-termmemorymodel","venue":null,"work_id":"6b3708a2-6040-4174-848f-61be0788cbcb","year":2020},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.241963Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:530fa0c7ed1458647ea3a7417da0e2bd14a23f7abf44c30b2b4cd216ad8f9817","observation_id":"7ed96e37-7c0f-43c2-ae9e-6ad0442be7f8","resolution":{"observed_at":"2026-08-06T16:45:06.732504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.247296Z","title":"At- tention is all you need.Advances in neural information processing systems, 30, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.247296Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:0cd52fdc8b917009cf93ed1696bbd184b1814e57782e0c9e674afd498e1d339e","observation_id":"c65184e7-79a3-4378-8369-f4f4c1fdbf4e","resolution":{"observed_at":"2026-08-06T16:45:06.247296Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.01271","last_updated":"2018-04-19T14:32:38Z","snapshot_observed_at":"2026-08-13T10:37:24.864456Z","submitted_at":"2018-03-04T00:20:29Z","title":"An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.01271","snapshot_observed_at":"2026-08-06T16:45:06.252312Z","title":"An empirical eval- uation of generic convolutional and recurrent networks for sequence modeling","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.252312Z"},"links":{"cited_paper":"/paper/1803.01271","citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:e52d28f702062c496a6e581cd8e88b9038157b36d0deaf26eda6c640e54b0718","observation_id":"1da858b1-965f-444c-b518-8fdc2e66a16e","resolution":{"observed_at":"2026-08-06T16:45:06.252312Z","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":"2026-08-06T16:45:06.678056Z","title":"In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 3521–3529, 2018","venue":null,"work_id":"a2885aaf-4453-469f-9026-e132460f2c28","year":2018},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.257085Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:ae48d7d19f8e88ce0727ba0809ff4599fc8136e81b185a6d009492e27db4ea0e","observation_id":"368ba664-8337-48f4-8dc6-851fbab27e42","resolution":{"observed_at":"2026-08-06T16:45:06.688782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-06T16:45:06.652021Z","title":"A multi- modal architecture with spatio-temporal-text adaptation for video- basedtrafficaccidentanticipation","venue":null,"work_id":"3ee2516d-eb6b-4336-852c-3da47b4749a9","year":2025},"citing_paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T16:45:06.262282Z"},"links":{"citing_paper":"/paper/2507.12762"},"observation_digest":"sha256:fc7d8c80be35d29620321a4ea0d0914e2d6f94d0f4303a57a7a4f0a10eb47b8a","observation_id":"3464c829-afbd-43d9-ae8e-aa28437565a5","resolution":{"observed_at":"2026-08-06T16:45:06.662684Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.12762","last_updated":"2025-07-17T03:34:54Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T19:43:50.186794Z","submitted_at":"2025-07-17T03:34:54Z","title":"World Model-Based End-to-End Scene Generation for Accident Anticipation in Autonomous Driving"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":42},"total_outbound_references":60},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2507.12762."}