{"as_of":"2026-08-08T21:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cd4887992f344bfcc211e88772d10d9c7e8ecb3456e79e9deacda35e0430fe3f","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":29,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T20:07:09.361168Z","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":"2026-07-04T16:29:56.718409Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2310.04378","last_updated":"2023-10-06T17:11:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-06T17:11:58Z","title":"Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-05-13T04:15:54.681913Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2310.04378"},"observation_digest":"sha256:013eb1a413e957482aa0e884de156cf0d4fc9d7e2f8cff4add64ca5da1135662","observation_id":"7498afc4-dcd6-4e4c-84bc-91ea474d999e","resolution":{"observed_at":"2026-05-13T04:15:54.759660Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2402.13243","last_updated":"2026-04-17T23:12:55Z","snapshot_observed_at":"2026-08-04T01:21:26.466156Z","submitted_at":"2024-02-20T18:55:09Z","title":"VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-24T03:16:03.058129Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2402.13243"},"observation_digest":"sha256:5ce5bd03e3e0dc15e04c1b437fe1a3cb239ff73e931496307bc3e52b539d46d5","observation_id":"dbc7e035-086f-43f0-b48d-f061ca7a44e9","resolution":{"observed_at":"2026-05-24T03:18:49.496542Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2410.22313","last_updated":"2024-10-29T17:53:56Z","snapshot_observed_at":"2026-07-31T01:16:26.372370Z","submitted_at":"2024-10-29T17:53:56Z","title":"Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-15T15:24:23.756052Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2410.22313"},"observation_digest":"sha256:bf1a5d690fd8d116632c5a59ec8c1b20f488265944f72648d69ac3ea8553b35b","observation_id":"4a62545b-6cfa-430a-a850-97b0afe59c3e","resolution":{"observed_at":"2026-05-15T15:24:23.933893Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-07T20:07:09.361168Z","title":"Multipath: Multiple probabilistic anchor trajectory hypothe- ses for behavior prediction","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2502.12178","last_updated":"2025-02-14T05:29:43Z","snapshot_observed_at":"2026-08-07T19:59:39.874736Z","submitted_at":"2025-02-14T05:29:43Z","title":"Direct Preference Optimization-Enhanced Multi-Guided Diffusion Model for Traffic Scenario Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T20:07:09.361168Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2502.12178"},"observation_digest":"sha256:f2b95118f1a23baa0ed4b157abe2f3f3f5abbc888a2150160551a9185964122b","observation_id":"d9c88809-4477-4b2e-8143-814d43366375","resolution":{"observed_at":"2026-08-07T20:07:09.361168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2503.19755","last_updated":"2025-03-25T15:18:43Z","snapshot_observed_at":"2026-08-05T21:57:39.132989Z","submitted_at":"2025-03-25T15:18:43Z","title":"ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-17T08:10:39.240168Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2503.19755"},"observation_digest":"sha256:90e2444bdaaedcb8d26d85ec8a258b64abc191852fe2036d4a021c14940d5382","observation_id":"2d9efd70-a94a-4ae1-9f7d-233839ac33a2","resolution":{"observed_at":"2026-05-17T08:10:39.336650Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-07T15:16:11.155330Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.15703","last_updated":"2025-05-21T16:16:52Z","snapshot_observed_at":"2026-08-08T16:09:42.447270Z","submitted_at":"2025-05-21T16:16:52Z","title":"HAMF: A Hybrid Attention-Mamba Framework for Joint Scene Context Understanding and Future Motion Representation Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:16:11.155330Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2505.15703"},"observation_digest":"sha256:1992bfde6efe67ae2f421085d91bb0ef5b2d3626537b4c7f9578a1523cd14b6b","observation_id":"e8881259-4ea7-4196-834e-29a720aa3a1f","resolution":{"observed_at":"2026-08-07T15:16:11.155330Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-07T13:47:09.742266Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction.arXiv preprint arXiv:1910.05449, 2019","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.21581","last_updated":"2026-06-25T02:34:38Z","snapshot_observed_at":"2026-08-07T13:40:30.128108Z","submitted_at":"2025-05-27T09:58:43Z","title":"CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving","version":4},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:47:09.742266Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2505.21581"},"observation_digest":"sha256:10d33a248d93902bd43b11a04b2490286d1da0e12af0540a75dc46bb460e4e34","observation_id":"100a528b-3082-4f39-aa15-c53caa46a017","resolution":{"observed_at":"2026-08-07T13:47:09.742266Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-07T12:45:48.781737Z","title":"Shaoyu Chen, Bo Jiang, Hao Gao, Bencheng Liao, Qing Xu, Qian Zhang, Chang Huang, Wenyu Liu, and Xinggang Wang","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.23612","last_updated":"2025-05-29T16:19:59Z","snapshot_observed_at":"2026-08-07T12:39:52.884822Z","submitted_at":"2025-05-29T16:19:59Z","title":"Autoregressive Meta-Actions for Unified Controllable Trajectory Generation","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:48.781737Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2505.23612"},"observation_digest":"sha256:3f280b8a03f7f1db21e83ee85fbb533c6597dd8d79a1e947df23f8a232c88c38","observation_id":"98a226a5-c546-4b57-973a-f71d66953428","resolution":{"observed_at":"2026-08-07T12:45:48.781737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2506.08052","last_updated":"2025-09-29T17:21:41Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-09T03:14:04Z","title":"ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-15T07:36:24.319361Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2506.08052"},"observation_digest":"sha256:4f48428881a844343aa6e048c301d14bd66c3972f1f067750db9edbbbc848408","observation_id":"7d81486f-8bef-4fb7-a4f5-f0287779a421","resolution":{"observed_at":"2026-05-15T07:36:24.379941Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-07T04:40:57.278839Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.10145","last_updated":"2026-06-04T05:42:29Z","snapshot_observed_at":"2026-08-07T04:30:52.642430Z","submitted_at":"2025-06-11T19:50:23Z","title":"RoCA: Robust Cross-Domain End-to-End Autonomous Driving","version":3},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T04:40:57.278839Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2506.10145"},"observation_digest":"sha256:fc5af345449ba1964ea10b2b6c7259f7dc7b2e316cee91b6f56cb014c0c777b3","observation_id":"957dc1fc-df82-483d-9507-51814199cd0c","resolution":{"observed_at":"2026-08-07T04:40:57.278839Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-06T23:49:13.253143Z","title":"Available: https://arxiv.org/abs/1910.05449","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.16336","last_updated":"2025-06-19T14:14:55Z","snapshot_observed_at":"2026-08-08T07:57:08.740974Z","submitted_at":"2025-06-19T14:14:55Z","title":"Goal-conditioned Hierarchical Reinforcement Learning for Sample-efficient and Safe Autonomous Driving at Intersections","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-06T23:49:13.253143Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2506.16336"},"observation_digest":"sha256:9504cd1f2cd23a55a490038fd1684d75b604cc46e62fb7b99543b5596ab2538c","observation_id":"09da6045-488f-4dcb-ab9f-b449363a2107","resolution":{"observed_at":"2026-08-06T23:49:13.253143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-06T19:56:40.441830Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction.arXiv preprint arXiv:1910.05449, 2019","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2507.04263","last_updated":"2025-07-06T06:45:14Z","snapshot_observed_at":"2026-08-08T11:54:35.112818Z","submitted_at":"2025-07-06T06:45:14Z","title":"SRefiner: Soft-Braid Attention for Multi-Agent Trajectory Refinement","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:56:40.441830Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2507.04263"},"observation_digest":"sha256:96a98599170bddd151e1a77fa686293f7a8fbe08cdc70e407aeecd639db00178","observation_id":"afff6e9d-37b8-4f8c-a3bf-0eac919a196c","resolution":{"observed_at":"2026-08-06T19:56:40.441830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-06T19:07:15.397231Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2507.06531","last_updated":"2025-07-09T04:18:01Z","snapshot_observed_at":"2026-08-06T18:58:56.063579Z","submitted_at":"2025-07-09T04:18:01Z","title":"ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention Capture","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:07:15.397231Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2507.06531"},"observation_digest":"sha256:a033ed1ed3b12d24e6861877e14dc32176b4eda4a83826275870cd7fbc21793f","observation_id":"17254ada-b175-411d-9e47-4e8ad90e3fc5","resolution":{"observed_at":"2026-08-06T19:07:15.397231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-06T16:59:54.485669Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2507.12083","last_updated":"2025-07-16T09:46:17Z","snapshot_observed_at":"2026-08-08T16:09:42.972551Z","submitted_at":"2025-07-16T09:46:17Z","title":"Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:59:54.485669Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2507.12083"},"observation_digest":"sha256:af70ed836d3383c3bb235bceb6ed5818949c7d438e6947b3e2c43ea4f0cb368d","observation_id":"9e635c8f-2ac5-4687-8221-b84e63ad6944","resolution":{"observed_at":"2026-08-06T16:59:54.485669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-06T14:13:03.903985Z","title":null,"venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2507.19701","last_updated":"2025-07-25T22:45:42Z","snapshot_observed_at":"2026-08-08T06:22:03.555253Z","submitted_at":"2025-07-25T22:45:42Z","title":"PhysVarMix: Physics-Informed Variational Mixture Model for Multi-Modal Trajectory Prediction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T14:13:03.903985Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2507.19701"},"observation_digest":"sha256:3f3ad2c2659f54107a21dfd626c3cf1a1e175494de4daa15fe63f9f73b82c65e","observation_id":"2b7ec655-202e-4893-a459-82997c26c408","resolution":{"observed_at":"2026-08-06T14:13:03.903985Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-06T05:33:57.854132Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2508.01585","last_updated":"2025-08-03T04:53:39Z","snapshot_observed_at":"2026-08-07T05:22:29.662459Z","submitted_at":"2025-08-03T04:53:39Z","title":"A Spatio-temporal Continuous Network for Stochastic 3D Human Motion Prediction","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T05:33:57.854132Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2508.01585"},"observation_digest":"sha256:f371f0021b9040552c9fd87e782e5aa8fe1bd26b4fd14c59a891270f4cd8af35","observation_id":"5fcff8f1-6666-4cd1-9274-c4dd65ae98e5","resolution":{"observed_at":"2026-08-06T05:33:57.854132Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-05T16:50:01.098425Z","title":"Multipath: Multiple probabilistic anchor trajec- tory hypotheses for behavior prediction,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2508.17797","last_updated":"2025-08-25T08:43:08Z","snapshot_observed_at":"2026-08-07T18:18:29.062194Z","submitted_at":"2025-08-25T08:43:08Z","title":"Adaptive Output Steps: FlexiSteps Network for Dynamic Trajectory Prediction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T16:50:01.098425Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2508.17797"},"observation_digest":"sha256:db947de3eefa329cf6ebc2b939c01811d0da6b40f7118602f57f6c66f3232b0f","observation_id":"e93793cd-fb8c-40d8-a923-b1b292b09415","resolution":{"observed_at":"2026-08-05T16:50:01.098425Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2603.24155","last_updated":"2026-04-07T08:33:33Z","snapshot_observed_at":"2026-07-06T22:50:28.640006Z","submitted_at":"2026-03-25T10:24:16Z","title":"Goal-Oriented Reactive Simulation for Closed-Loop Trajectory Prediction","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-15T00:55:01.446865Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2603.24155"},"observation_digest":"sha256:3fb3fa2cbba31b855decc13a5ae91198bdbef373d4493c33802e0727b420e026","observation_id":"37fbfe0a-46f7-4054-af8c-daf5d69c605d","resolution":{"observed_at":"2026-05-15T00:58:26.223278Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2604.04573","last_updated":"2026-04-06T10:09:24Z","snapshot_observed_at":"2026-07-06T22:53:33.177713Z","submitted_at":"2026-04-06T10:09:24Z","title":"SAIL: Scene-aware Adaptive Iterative Learning for Long-Tail Trajectory Prediction in Autonomous Vehicles","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-10T19:31:42.519478Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2604.04573"},"observation_digest":"sha256:3d77dcd970bbf3f5b78176412a7a7230dbd169b00170d29aacf05345e9df4e28","observation_id":"6a0aa7d5-adf8-44c5-ba8b-b4c98f0bb929","resolution":{"observed_at":"2026-05-10T22:50:50.869193Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2604.16783","last_updated":"2026-04-18T02:13:02Z","snapshot_observed_at":"2026-07-06T23:04:01.558812Z","submitted_at":"2026-04-18T02:13:02Z","title":"EdgeVTP: Exploration of Latency-efficient Trajectory Prediction for Edge-based Embedded Vision Applications","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T07:53:01.735375Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2604.16783"},"observation_digest":"sha256:7c5348401fd8cba1d89f28acc360dc666893554836f346984ca0646cc68da387","observation_id":"a5700cec-b0f7-4848-9b26-9c3b4f9f5137","resolution":{"observed_at":"2026-05-10T09:18:32.375802Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2604.18126","last_updated":"2026-04-20T11:44:16Z","snapshot_observed_at":"2026-07-31T17:39:47.589084Z","submitted_at":"2026-04-20T11:44:16Z","title":"Chatting about Conditional Trajectory Prediction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T04:17:58.564914Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2604.18126"},"observation_digest":"sha256:a71f21ca90b8264ad1a73e02e9b303bd98785499a6ea6eaf43b51221aaa650b4","observation_id":"cdec73a1-90fa-46fe-a9ca-8e6bc0769e66","resolution":{"observed_at":"2026-05-11T12:01:06.298337Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2605.12625","last_updated":"2026-05-14T17:58:42Z","snapshot_observed_at":"2026-07-06T23:24:18.302402Z","submitted_at":"2026-05-12T18:10:19Z","title":"Driving Intents Amplify Planning-Oriented Reinforcement Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-14T20:50:14.602822Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2605.12625"},"observation_digest":"sha256:6d66986f48145248e11a77c69a81640dba4c39837aa476ffc156a88f323d94f3","observation_id":"5d3c6ab9-3f32-4d68-9734-dbd23bfa18a9","resolution":{"observed_at":"2026-05-14T20:52:58.747807Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2605.12625","last_updated":"2026-05-14T17:58:42Z","snapshot_observed_at":"2026-07-06T23:24:18.302402Z","submitted_at":"2026-05-12T18:10:19Z","title":"Driving Intents Amplify Planning-Oriented Reinforcement Learning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-15T04:58:07.943615Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2605.12625"},"observation_digest":"sha256:c131495014afeb7a01104f1278369155be3bf3e7d65dd0c9289976f0eca3db37","observation_id":"9c5ca670-ed91-489c-a9d7-c722a1af30dc","resolution":{"observed_at":"2026-05-15T04:59:45.539399Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2605.29705","last_updated":"2026-05-28T10:04:02Z","snapshot_observed_at":"2026-08-07T00:41:33.225628Z","submitted_at":"2026-05-28T10:04:02Z","title":"BitTP: The Lightweight Trajectory Prediction Model with BitLLM for Edge-Devices","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-29T07:56:00.180707Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2605.29705"},"observation_digest":"sha256:049bb276e704aa45c9f7c2dfa281a4375419935a041903eb20059ef89b9301c5","observation_id":"55d6660e-aaa9-4edd-af21-d2e560b18813","resolution":{"observed_at":"2026-06-29T08:03:14.567690Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2606.24101","last_updated":"2026-06-23T03:30:20Z","snapshot_observed_at":"2026-08-02T03:37:38.259529Z","submitted_at":"2026-06-23T03:30:20Z","title":"NavWM: A Unified Navigation World Model for Foresight-Driven Planning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-26T00:42:30.237545Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2606.24101"},"observation_digest":"sha256:92f5cddfe4f70bbc3488004ca63a7e35ddf7569e40c753977aa600783de77005","observation_id":"4d2f0e47-3315-4ec8-8688-b98509a06fad","resolution":{"observed_at":"2026-07-04T16:29:56.720051Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":"1910.05449","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-04T16:29:56.718409Z","title":"Multipath: Multiple probabilistic anchor tra- jectory hypotheses for behavior prediction","venue":null,"work_id":"59b25b75-4902-4916-8d3d-9dda92131398","year":1910},"citing_paper":{"arxiv_id":"2606.26424","last_updated":"2026-06-24T22:26:43Z","snapshot_observed_at":"2026-08-07T22:43:50.121138Z","submitted_at":"2026-06-24T22:26:43Z","title":"Rethinking Training & Inference for Forecasting: Linking Winner-Take-All back to GMMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-26T01:16:40.007718Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2606.26424"},"observation_digest":"sha256:cc4ff375072f2327e9097e9a2e2ddd50810ca55950781c66b3848619550a9f97","observation_id":"d4e2b13e-5f03-468a-ba3c-fe6f9ab62b62","resolution":{"observed_at":"2026-07-04T15:49:58.057027Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-11T13:09:16.091741Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.04812","last_updated":"2026-07-06T08:47:56Z","snapshot_observed_at":"2026-08-06T17:31:45.618265Z","submitted_at":"2026-07-06T08:47:56Z","title":"TGRIP: A Text-Guided Approach to Vehicle Instance Prediction in Autonomous Driving","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-11T13:09:16.091741Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2607.04812"},"observation_digest":"sha256:f3b17f291b12e9103beefaba24f769548d57c744b7bf97c4857a9cb82695db4c","observation_id":"e66280e1-5c93-4b6d-80ac-7c8d04062adc","resolution":{"observed_at":"2026-07-11T13:09:16.091741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-07-14T16:37:01.846968Z","title":"arXiv preprint arXiv:1910.05449 , year=","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.09740","last_updated":"2026-07-02T23:55:53Z","snapshot_observed_at":"2026-08-07T12:52:02.711048Z","submitted_at":"2026-07-02T23:55:53Z","title":"A Dynamic Scene Interaction Reasoning Framework for Scene-level Lane-Change Intention and Trajectory Prediction of Multiple Interacting Vehicles","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-07-14T16:37:01.846968Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2607.09740"},"observation_digest":"sha256:6741bcccd7489131cae8f2648f6c8c32be41536b9c589fdca22f8c3cab8e289b","observation_id":"f4ddec34-db7f-4613-ba6d-ac377f0cedbe","resolution":{"observed_at":"2026-07-14T16:37:01.846968Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05449","snapshot_observed_at":"2026-08-05T17:29:21.061148Z","title":"Multipath: Multiple probabilistic anchor trajectory hypotheses for behavior prediction.arXiv preprint arXiv:1910.05449,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.03521","last_updated":"2026-08-04T12:05:15Z","snapshot_observed_at":"2026-08-08T14:01:33.545759Z","submitted_at":"2026-08-04T12:05:15Z","title":"Pivot-Centric Trajectory Prediction: Bridging Long Horizons via Dynamical Guidance","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-05T17:29:21.061148Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2608.03521"},"observation_digest":"sha256:3bd21b7a6e6d753905ed1caad6e9c8bcf82fccae79c7c4b9b1555c154f829c10","observation_id":"291c3adc-7fb0-48be-954a-c082873c6de4","resolution":{"observed_at":"2026-08-05T17:29:21.061148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1910.05449/citation-record","integrity":"/paper/1910.05449/integrity","json":"/paper/1910.05449/citation-record.json","paper":"/paper/1910.05449"},"outbound":[],"paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T23:16:21.521818Z","submitted_at":"2019-10-12T00:34:37Z","title":"MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:1910.05449."}