{"as_of":"2026-08-13T04:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2d5a0c644f4235c5fb72a1a95d7b437dbaa317e182c6b09c8e72aacc79b54f1f","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:11:49.423780Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:11:49.423780Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-12T13:11:49.457598Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"cited_work":{"arxiv_id":"2411.16457","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.16457","snapshot_observed_at":"2026-08-12T13:11:49.457598Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","venue":"cs.RO","work_id":"f2c2d052-b834-461a-820a-dea69f429694","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.423780Z"},"links":{"cited_paper":"/paper/2411.16457","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:7e7615f8dc1096b0f2761e5be8fb969c10da965f39899aa4533f2eec9259c393","observation_id":"008b2a9e-db5f-43e9-86d8-63602a8d6323","resolution":{"observed_at":"2026-08-12T13:11:49.464108Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.16457/citation-record","integrity":"/paper/2411.16457/integrity","json":"/paper/2411.16457/citation-record.json","paper":"/paper/2411.16457"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:11:50.212985Z","title":"A survey on trajectory-prediction methods for autonomous driving,","venue":null,"work_id":"a0863fa9-193b-4c18-8cd9-c55ebb90fd3f","year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.182745Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:c9f93f222925a113f9b0463fa24790dc75f9f9fd9b6244c6e387d5ea83c48e6f","observation_id":"3c861e09-bd18-49f7-8994-c6cac2e2d845","resolution":{"observed_at":"2026-08-12T13:11:50.216419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.200225Z","title":"Mftraj: Map-free, behavior-driven trajectory prediction for autonomous driving,","venue":null,"work_id":"444c7936-8df0-4962-b6ad-af13a4e8d309","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.187632Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:3a224012cb5125ad73ff484d25529e40496d302fbea026d66a05b78cc6e3b320","observation_id":"7ba8e632-b64f-4f3d-b399-9d32863c7313","resolution":{"observed_at":"2026-08-12T13:11:50.204697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.187244Z","title":"Physics-informed trajectory prediction for au- tonomous driving under missing observation,","venue":null,"work_id":"26897e5a-91be-4748-bf81-d1e476ac6a24","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.192887Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:1b5eb85e25e1363751ba76ccc76b70eb665566aeccd763186cca777c9d6a3167","observation_id":"be762fa0-ec2a-4482-929e-ac81b99bb1f8","resolution":{"observed_at":"2026-08-12T13:11:50.191865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2312.03543","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:11:49.645742Z","title":"GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Atten- tion with Large Language Models,","venue":null,"work_id":"cfa1e2ff-90a4-4758-a45a-503d0c6e570f","year":2023},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.198490Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:8fd41706b2aef53b50ba536518f685e9bbcd76ff6cee97ffb8fc8867857ea3d6","observation_id":"98073373-6109-4b19-9a12-b7c50b1744c6","resolution":{"observed_at":"2026-08-12T13:11:49.652729Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.17520","last_updated":"2024-04-26T16:40:01Z","snapshot_observed_at":"2026-08-13T00:20:44.785621Z","submitted_at":"2024-04-26T16:40:01Z","title":"A Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environment","version":1},"cited_work":{"arxiv_id":"2404.17520","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.17520","snapshot_observed_at":"2026-08-12T13:11:49.569840Z","title":"A Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environment","venue":"cs.RO","work_id":"f2d057f4-580f-40c6-a778-d9981b9c5000","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.202404Z"},"links":{"cited_paper":"/paper/2404.17520","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:577510a34f13071a53098660b7db381249e67071b6d3fef194637a31e0db5f06","observation_id":"fbe70d82-9bcb-46a2-93b1-9505f12425e2","resolution":{"observed_at":"2026-08-12T13:11:49.574379Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.175768Z","title":"Uncertainty-aware driver trajectory prediction at urban intersections,","venue":null,"work_id":"cff7ede2-28ab-4254-bee4-f110b3669ee8","year":2019},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.207801Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:a18c84bb01000e7b777313fbb6208b572940c7229c929074dbb1ffbd22b3aa99","observation_id":"a010f059-c30e-4b3c-9e46-29957d70fd93","resolution":{"observed_at":"2026-08-12T13:11:50.179986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.163027Z","title":"Bat: Behavior-aware human-like trajectory prediction for autonomous driving,","venue":null,"work_id":"9d9660e9-6604-4f59-952e-3b76fc31a7a4","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.213263Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:e0dc56dbca2b9cb0f4a4acc65d187d2caf81e6ba977290c6a947b5956dd66f4d","observation_id":"65e3c190-4270-4a7c-b9d4-caa7c6a0cb4a","resolution":{"observed_at":"2026-08-12T13:11:50.168145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.150220Z","title":"Gpt-4 enhanced multimodal grounding for au- tonomous driving: Leveraging cross-modal attention with large language models,","venue":null,"work_id":"3db34a48-afbd-49ff-8d62-6e0f5d195138","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.217652Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:15c8e36864b92381f40c2dd991e0b7da58f4327783fb964f991d48921297d416","observation_id":"5aad141d-b5f7-40d1-acb4-42c0b0e069b2","resolution":{"observed_at":"2026-08-12T13:11:50.154964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04318","last_updated":"2024-03-08T14:13:01Z","snapshot_observed_at":"2026-08-13T04:24:52.992299Z","submitted_at":"2024-02-06T19:02:33Z","title":"Human Observation-Inspired Trajectory Prediction for Autonomous Driving in Mixed-Autonomy Traffic Environments","version":2},"cited_work":{"arxiv_id":"2402.04318","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.04318","snapshot_observed_at":"2026-08-12T13:11:49.551565Z","title":"Human Observation-Inspired Trajectory Prediction for Autonomous Driving in Mixed-Autonomy Traffic Environments","venue":"cs.RO","work_id":"29bb9394-3bce-44ff-8671-50dee740f1c2","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.222347Z"},"links":{"cited_paper":"/paper/2402.04318","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:e88766145ee8f8544a26a0876741fdd0c5edc1983c1934f131505733965aa405","observation_id":"8aaead06-e520-4398-b683-b125b7e0e7f6","resolution":{"observed_at":"2026-08-12T13:11:49.556996Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.138959Z","title":"A cognitive-based trajectory prediction ap- proach for autonomous driving,","venue":null,"work_id":"00ecc73a-45e6-4531-845d-75db7e4d4dc7","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.228772Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:7c8a0aa44c516b4ae1a3ef9fd2b4c9cf6892021272992d3ebdfc83fc63e6dda7","observation_id":"5849754c-52b8-479b-8d0d-28f4e843a224","resolution":{"observed_at":"2026-08-12T13:11:50.142771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.126301Z","title":"Diverse and admissible trajectory forecasting through multi- modal context understanding,","venue":null,"work_id":"d572da9d-a4cb-41c1-b72f-a111fcab29e6","year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.233674Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:5a2d0937ff903e2c4cd238c24ef1fa6d36237e678af6f07dfaa2e489743fc676","observation_id":"3ceba366-c589-4d97-ba95-7ece0ab514fa","resolution":{"observed_at":"2026-08-12T13:11:50.130585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.113835Z","title":"Extended kalman ﬁlter for state estimation and trajectory predic- tion of a moving object detected by an unmanned aerial vehicle,","venue":null,"work_id":"3cd9df6f-7b44-4cd5-92e2-0317ee24c39a","year":2007},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.238309Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:341062d0207b40a356a4f2ca075b7bf06c4b37403dbc88a25dbf70069eb00a7e","observation_id":"ef2905cb-9066-4ddd-a733-dc28e0ec4bf5","resolution":{"observed_at":"2026-08-12T13:11:50.118515Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.100523Z","title":"Probabilistic vehicle trajectory predic- tion over occupancy grid map via recurrent neural net- work,","venue":null,"work_id":"df956893-a4c3-42c0-93c2-f5e5c371f98a","year":2017},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.242210Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:9ed794ee933541b5af55896950b103ac6a8d659cbf08f75dd51cd7a9029fe4eb","observation_id":"0c441bd7-16db-43c7-9ef2-c3e0c416546a","resolution":{"observed_at":"2026-08-12T13:11:50.105058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.087623Z","title":"An lstm network for highway trajectory prediction,","venue":null,"work_id":"f3081fad-405d-4b0f-aa15-cc96a57c3fbb","year":2017},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.247391Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:1acee8b2e2efcc7e7a85930db657dbedb6e5cbd9090eaeb964834771616805bb","observation_id":"823218c3-9551-47a1-a6cf-d8941e5561ea","resolution":{"observed_at":"2026-08-12T13:11:50.092115Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.075323Z","title":"Social lstm: Human tra- jectory prediction in crowded spaces,","venue":null,"work_id":"3b569b5e-817b-402f-bbcf-63274548339a","year":2016},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.252725Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:0f3edfda41fb9bd11bfe8a9916f5f07bb101de18509eea643d530946db5aa570","observation_id":"1ee99575-e0a5-47fd-bbd6-d9e81bed7d68","resolution":{"observed_at":"2026-08-12T13:11:50.079754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.062928Z","title":"Ast-gnn: An attention-based spatio- temporal graph neural network for interaction-aware pedestrian trajectory prediction,","venue":null,"work_id":"2f80f35a-f0c4-4795-920a-572db201e2f4","year":2021},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.256945Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:e9fbb02217b9b5a3333ce85a6cb2acf683930f50366f0114d386f57ca479184c","observation_id":"26816278-6a50-4e77-994b-346f7349055f","resolution":{"observed_at":"2026-08-12T13:11:50.067020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.050409Z","title":"Goal-gan: Multimodal trajectory prediction based on goal position estimation,","venue":null,"work_id":"c7df20d8-6aaa-4729-81eb-3c6bcaa9330c","year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.261729Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:9d634cc1f654c8d9e91cf6050d052cb35e23737ebebd14f4b5703f868174c332","observation_id":"aa26087e-d037-4c2e-9755-be6769015159","resolution":{"observed_at":"2026-08-12T13:11:50.055005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.036453Z","title":"Desire: Distant future prediction in dynamic scenes with interacting agents,","venue":null,"work_id":"edd935f9-3c89-48d4-bb93-cdbbdeefe7f8","year":2017},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.266864Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:853a9658dd4f8f76faa69d3d1f80b0068654b47473f568ffd9eb6b1087ef2693","observation_id":"2860c193-87df-4152-b45b-28171ad0fb82","resolution":{"observed_at":"2026-08-12T13:11:50.041459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.06125","last_updated":"2022-04-13T01:10:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-13T01:10:33Z","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.06125","snapshot_observed_at":"2026-08-12T13:11:49.271025Z","title":"Hierarchical text-conditional im- age generation with clip latents,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.271025Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:74bdd812a38ed9fb60fef86c89ff148e8f37d0f6a7ff7b53141c5e75c4fd709d","observation_id":"e6dee0dc-932f-4612-8e03-c0f7aac82e91","resolution":{"observed_at":"2026-08-12T13:11:49.271025Z","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":"2026-08-12T13:11:50.020241Z","title":"High-resolution image synthesis with la- tent diffusion models,","venue":null,"work_id":"16ec2107-0d38-4ea5-94c2-6c2530b945c4","year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.275502Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:4007f990411090961129cd64faf475cd589b6b78a0ca47f4353d9fcc4fb7c174","observation_id":"8ba67f73-6c28-4564-9431-307190de7f14","resolution":{"observed_at":"2026-08-12T13:11:50.024991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:50.007530Z","title":"Photorealistic text- to-image diffusion models with deep language under- standing,","venue":null,"work_id":"e62d1b00-cb56-4bb1-b62e-87f9c3995972","year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.280434Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:ec701bd6b2d1306b4e7b4e078393bfaa4f18c992c615e3dceb0ab40b8a3eef99","observation_id":"8778feb4-7b97-43ff-8d3e-fd0d0221e46d","resolution":{"observed_at":"2026-08-12T13:11:50.011631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02303","last_updated":"2022-10-05T14:41:38Z","snapshot_observed_at":"2026-07-06T13:59:57.800591Z","submitted_at":"2022-10-05T14:41:38Z","title":"Imagen Video: High Definition Video Generation with Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.02303","snapshot_observed_at":"2026-08-12T13:11:49.285444Z","title":"Imagen video: High deﬁnition video generation with diffusion models,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.285444Z"},"links":{"cited_paper":"/paper/2210.02303","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:fc82dff525b3b5a470560394761ca233922571490600fc9ef88eab6f314dd843","observation_id":"37539985-5b49-4e94-b9e7-40390df3786e","resolution":{"observed_at":"2026-08-12T13:11:49.285444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.09481","last_updated":"2022-12-08T01:18:55Z","snapshot_observed_at":"2026-08-07T11:16:36.992883Z","submitted_at":"2022-03-16T03:52:45Z","title":"Diffusion Probabilistic Modeling for Video Generation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.09481","snapshot_observed_at":"2026-08-12T13:11:49.290864Z","title":"Diffusion prob- abilistic modeling for video generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.290864Z"},"links":{"cited_paper":"/paper/2203.09481","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:4063acfcd34806419b48373786b29476eb8af38f465541223a3e2f6c2ad170dd","observation_id":"d37176e8-23a2-4f48-8e63-9e7343a98cc5","resolution":{"observed_at":"2026-08-12T13:11:49.290864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14988","last_updated":"2022-09-29T17:50:40Z","snapshot_observed_at":"2026-07-06T13:57:54.539656Z","submitted_at":"2022-09-29T17:50:40Z","title":"DreamFusion: Text-to-3D using 2D Diffusion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14988","snapshot_observed_at":"2026-08-12T13:11:49.295068Z","title":"Dreamfusion: Text-to-3d using 2d diffusion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.295068Z"},"links":{"cited_paper":"/paper/2209.14988","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:af6d1561eb36738ccd6855461584c9de5d7a2944b3591a41e21e7eb0e9660bb5","observation_id":"b4591648-6ef0-4fed-97ac-351ab5fde5ba","resolution":{"observed_at":"2026-08-12T13:11:49.295068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:11:49.299429Z","title":"Denoising diffusion probabilistic models,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.299429Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:b574f55b54e22b08a95f2ea5bd9bdaeedf8ddeceeb39248156c145fbab97041f","observation_id":"f3b1605b-c543-4cb3-87f7-22cc7901c48b","resolution":{"observed_at":"2026-08-12T13:11:49.299429Z","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":"2026-08-12T13:11:49.986062Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics,","venue":null,"work_id":"98516b39-3279-4589-a5b3-0f96bb271c2c","year":2015},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.304154Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:3b2da868ddfaa97d3ac889414bc8ebbabc3bad06836ddff306e09aaca1134680","observation_id":"d8895922-594e-4b8e-ba39-41a0d33f8932","resolution":{"observed_at":"2026-08-12T13:11:49.990301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.973193Z","title":"Social gan: Socially acceptable trajectories with generative adversarial networks,","venue":null,"work_id":"6d7874da-4504-4d4c-8ab9-ac6a8396c667","year":2018},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.307605Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:ef32383f22ae2f3eaa2dc9088d2684649fc88be7c53c6dc28341b711714bd7b9","observation_id":"62f21691-a664-4ebd-b7f7-b3662ab21696","resolution":{"observed_at":"2026-08-12T13:11:49.977675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.961927Z","title":"Convolutional social pool- ing for vehicle trajectory prediction,","venue":null,"work_id":"87b5be4a-c5bf-4031-8f56-dcb1ffda322a","year":2018},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.312020Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:f2d045089e379e89a84bbf46a3133db37d95ef4453d6115517c08c109d4351d2","observation_id":"37e644a2-4fd4-4d29-bc13-797fa768d83b","resolution":{"observed_at":"2026-08-12T13:11:49.965721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.949872Z","title":"Multi-agent tensor fusion for contextual trajectory prediction,","venue":null,"work_id":"7409e737-36c7-4620-b191-21a921ca97e2","year":2019},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.315853Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:1b4a2a33c69ed4d85ec7c2858727033df465fc12d923ba5d4e6e83a5f54969ba","observation_id":"a01f8d66-d3d0-495c-a19f-f9ea1eeb9eb8","resolution":{"observed_at":"2026-08-12T13:11:49.954140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.936847Z","title":"Non-local social pooling for vehicle tra- jectory prediction,","venue":null,"work_id":"458e9ab7-1618-4444-9ef8-a2822a6e3c73","year":2019},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.319983Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:cdeb6bfffbf01b691a0e08f079b23455d9dd51308e372ebbb1f7c7dd031a9fbc","observation_id":"1eaa13c4-c91d-4b99-b5cf-e372df536a81","resolution":{"observed_at":"2026-08-12T13:11:49.941286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.924842Z","title":"Multi-modal trajectory pre- diction of surrounding vehicles with maneuver based lstms,","venue":null,"work_id":"9842909f-4893-4a65-9cbb-89e607fcff95","year":2018},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.323968Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:3cab76f7e939106c1e6fdceab04faeedba2dcc4c0e97667b61e71143afc406f4","observation_id":"d2a6bb7d-ad46-4f45-a77b-22111aff425d","resolution":{"observed_at":"2026-08-12T13:11:49.929020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.912499Z","title":"Interaction-aware motion prediction for au- tonomous driving: A multiple model kalman ﬁltering scheme,","venue":null,"work_id":"767b8856-3c32-4472-8bf9-bd9ae25ccc47","year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.328134Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:44bf3ab5cf24cf2c6bea52f960d4237b1e917bd1628b6f484a273516c5025c72","observation_id":"276e0adf-c466-46ba-8096-8e1e768d40be","resolution":{"observed_at":"2026-08-12T13:11:49.916469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.899457Z","title":"Imitating driver behavior with generative adversar- ial networks,","venue":null,"work_id":"48b526b9-c0ee-48a2-a2d0-2e8cd7dbe58d","year":2017},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.332429Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:0742544e03beffe50f6969facce994a9c85e4227df65725946df6d3a2007069c","observation_id":"291cff2e-3fdd-40f7-a3b5-a6c8732d4a85","resolution":{"observed_at":"2026-08-12T13:11:49.904013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.888334Z","title":"Multiple futures prediction,","venue":null,"work_id":"98d59a8e-14fe-404b-98b8-96ee70bea06e","year":2019},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.337680Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:036e1e4cda9a1d6f930a0d47b679c985cbfc062126edf8bcea1da9428862e53b","observation_id":"f9a42a32-769c-44a7-9bde-1523dedb0f34","resolution":{"observed_at":"2026-08-12T13:11:49.892049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.877014Z","title":"Dual transformer based prediction for lane change in- tentions and trajectories in mixed trafﬁc environment,","venue":null,"work_id":"2ac35362-9de0-4cde-a4e1-1186ed5533b1","year":2023},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.342582Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:6719ebfc24dfe12aeac264500db23beedca2baa3fc8111782aba165e4ab4b214","observation_id":"1a19cf52-96f0-4c4c-af40-29831cee9faf","resolution":{"observed_at":"2026-08-12T13:11:49.880826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.864309Z","title":"Neighbourhood context embeddings in deep inverse reinforcement learning for predicting pedestrian mo- tion over long time horizons,","venue":null,"work_id":"6b4e9787-0964-4d5b-9902-799b10295f76","year":2019},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.346726Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:2b11ba1fc3a1dbae2884b304f586ee18306d397f4281ff0998baaa8af13ae747","observation_id":"2da26c40-1b28-4640-960d-4ce27ddc5af1","resolution":{"observed_at":"2026-08-12T13:11:49.869432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.851959Z","title":"Wsip: Wave superposition inspired pooling for dynamic interactions-aware trajectory prediction,","venue":null,"work_id":"eb7bc33f-1e74-487c-a1a7-e2e42c6581b6","year":2023},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.350687Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:91abbfe8e896a262ba597e8242d30ad1913aaea3bf0e4deaf6800192e3ec27f3","observation_id":"147bb9e4-ef95-4d19-956d-a440cb357594","resolution":{"observed_at":"2026-08-12T13:11:49.855609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.840550Z","title":"Congestion-aware multi-agent trajectory prediction for collision avoidance,","venue":null,"work_id":"40693b37-13c1-4668-8244-3e0e325ac3d7","year":2021},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.354484Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:90ef9f36badaca6732dbd09e97c8b6ab0dd7cb52e128f5048143ebfccfb5050e","observation_id":"07080f56-f0a7-4cd8-b706-5c58c87f9054","resolution":{"observed_at":"2026-08-12T13:11:49.844341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.828838Z","title":"Attention based vehicle trajectory pre- diction,","venue":null,"work_id":"843e83a1-e6cd-4991-b22d-21ca72736592","year":2021},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.358072Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:b8e7aa2673e625c7621a370a3bd3a590bd48be833e8938f91efd6f814cbb1423","observation_id":"e8fdd59e-5d52-4b71-b7f7-01098ce951ba","resolution":{"observed_at":"2026-08-12T13:11:49.832784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.13324","last_updated":"2021-11-26T06:12:19Z","snapshot_observed_at":"2026-07-06T12:12:22.199519Z","submitted_at":"2021-11-26T06:12:19Z","title":"Hierarchical Motion Encoder-Decoder Network for Trajectory Forecasting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.13324","snapshot_observed_at":"2026-08-12T13:11:49.361792Z","title":"Hier- archical motion encoder-decoder network for trajectory forecasting,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.361792Z"},"links":{"cited_paper":"/paper/2111.13324","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:a8a89cf1794ed347ee60c0858cb0fe033fe6d3737fb62d580c9de1cdf6db85bf","observation_id":"d220a9cc-33f2-454e-9330-e8e3b103fee4","resolution":{"observed_at":"2026-08-12T13:11:49.361792Z","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":"2026-08-12T13:11:49.817536Z","title":"Multi-vehicle collaborative learning for trajectory pre - diction with spatio-temporal tensor fusion,","venue":null,"work_id":"36b152eb-3941-4299-ad4b-b4f6e5448bcf","year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.365621Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:4760a2770aa0db1b66722ea56b1534187fb3c275e306ba1f143b4aa9d4548624","observation_id":"f22000c4-7048-428f-9232-66c1224eb1c6","resolution":{"observed_at":"2026-08-12T13:11:49.821559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.806200Z","title":"Intention-aware vehicle trajectory prediction based on spatial-temporal dynamic attention network for internet of vehicles,","venue":null,"work_id":"6f5abb13-1c1e-4e26-9277-157453a8e245","year":2022},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.369929Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:c9def9744c83509625cd505ef28326176affd76854b6faf8109c5cfb40e45d59","observation_id":"6a8dffea-e08b-429f-85f9-5d42d3b8dbbc","resolution":{"observed_at":"2026-08-12T13:11:49.809768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.793203Z","title":"Environment-attention network for vehicle trajectory prediction,","venue":null,"work_id":"4ce4ea9a-59b2-46a0-96b7-dc1633c27346","year":2021},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.373376Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:bc24afb521d122dc37e6ccdc503492dc35105c5708365fd38cbadaa4a2012ca9","observation_id":"53fdb328-38e7-4f68-960b-f8dd11a3a089","resolution":{"observed_at":"2026-08-12T13:11:49.798124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1505.00853","last_updated":"2015-11-27T06:58:14Z","snapshot_observed_at":"2026-07-06T04:16:54.272660Z","submitted_at":"2015-05-05T01:16:39Z","title":"Empirical Evaluation of Rectified Activations in Convolutional Network","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.00853","snapshot_observed_at":"2026-08-12T13:11:49.378231Z","title":"Empirical evalu- ation of rectiﬁed activations in convolutional network,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.378231Z"},"links":{"cited_paper":"/paper/1505.00853","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:861b69219ab262c12e1ce3401a3d42ad539fdf2f8d7dd1cb3f85512867ce356f","observation_id":"eb993c68-d6b7-4392-b48e-6cb9ab5c74e5","resolution":{"observed_at":"2026-08-12T13:11:49.378231Z","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":"2026-08-12T13:11:49.780799Z","title":"An introductory survey on attention mecha- nisms in nlp problems,","venue":null,"work_id":"aaf8316e-45a5-4871-9c9b-32c3a7887b11","year":2019},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.382510Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:5da30fd3cf528e47396d85a9169a4f0e6a2df5ebe1a1f62c40debd1f4cb1539a","observation_id":"50dfc527-d37f-4de9-bb18-0f2781de5479","resolution":{"observed_at":"2026-08-12T13:11:49.784586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.769068Z","title":"Evolveg- raph: Multi-agent trajectory prediction with dynamic relational reasoning,","venue":null,"work_id":"4b899566-2697-427c-9bf5-23f7fc73c2b2","year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.386164Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:8012c6108d8ae989571433e80448d06560c81268ba00b0eb12fb92f77099f2b9","observation_id":"260f5b9c-dff0-4b24-b569-2b4005a6a770","resolution":{"observed_at":"2026-08-12T13:11:49.773084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.758430Z","title":"The highd dataset: A drone dataset of naturalistic ve- hicle trajectories on german highways for validation of highly automated driving systems,","venue":null,"work_id":"29a5aee5-1c7d-42e6-bcb4-57f6354f5f32","year":2018},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.389762Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:a2275fde3d413412c220a9407c42da56df31e12972314d9ac970c4223b3e265c","observation_id":"d5e5106f-534a-4c6c-a6e9-75e44df5055d","resolution":{"observed_at":"2026-08-12T13:11:49.761884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.746995Z","title":"Multiple knowledge representation of artiﬁcial intelligence,","venue":null,"work_id":"8e240843-3582-404c-96e3-84e98181c921","year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.393757Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:3c19e0b07d85bda6b94abd69b73e93bd1728954a4f31b5be32c4158679560efb","observation_id":"386ac329-399e-41d9-8d7d-9150d6e7b9ae","resolution":{"observed_at":"2026-08-12T13:11:49.750931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.734813Z","title":"Multi- head attention based probabilistic vehicle trajectory pre- diction,","venue":null,"work_id":"bbb7746e-542e-41d9-b224-b21f0c24ebe0","year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.397729Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:fe3d7798b0b30fe40c6adfb3b0cad57ba84889bdc96db522e861a9c8078af950","observation_id":"bfb7887d-ccc0-4d14-9581-40ad26587c4a","resolution":{"observed_at":"2026-08-12T13:11:49.739361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.722952Z","title":"Multi-vehicle collaborative learning for trajectory pre - diction with spatio-temporal tensor fusion,","venue":null,"work_id":"e8aa9250-75cc-4a92-bcba-f541d94f6ae0","year":2020},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.401904Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:3c6690bcc5f67578107a2096d15bf5e12fb0d5e65f3c6e82a9cbba8de8f883d3","observation_id":"7c743f6e-83e0-40fd-b80c-3a48bcce3945","resolution":{"observed_at":"2026-08-12T13:11:49.727229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.710709Z","title":"Root mean square error (rmse) or mean absolute error (mae),","venue":null,"work_id":"9c92beff-a0cf-4f55-b690-17472194d0a7","year":2014},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.405660Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:1fe740c8f540ccb793735fd7443932a99bda67fdc6bd27324dcd4948d94452da","observation_id":"3435e717-d56b-4791-a0a3-6189a91c6b4f","resolution":{"observed_at":"2026-08-12T13:11:49.715183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.698731Z","title":"Ss-lstm: A hierarchical lstm model for pedestrian trajectory predic- tion,","venue":null,"work_id":"c2df474a-1862-4b29-860f-5105e116d62f","year":2018},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.409303Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:3a5259f84fbc4bb1539d9946fac9e15ca01365f266aa98a7f1b5a88299771157","observation_id":"72549e85-d3e9-490a-8cc6-c9235b2f7110","resolution":{"observed_at":"2026-08-12T13:11:49.702720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.685934Z","title":"Encoding crowd interac- tion with deep neural network for pedestrian trajectory prediction,","venue":null,"work_id":"19b53ee7-ccb7-4be7-b199-e1e2ec612be3","year":2018},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.413595Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:e1111b237f8306aa406e5fb7431d680e65e5dddd301770968abf4ae6d2cbbf3e","observation_id":"f6381e38-2880-424f-acd5-a8d871af275b","resolution":{"observed_at":"2026-08-12T13:11:49.690628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.674626Z","title":"Dacr-amtp: adaptive multi-modal vehicle trajectory prediction for dynamic drivable areas based on collision risk,","venue":null,"work_id":"b1244b4c-b94e-4de1-8031-25813eb2acbd","year":2023},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.417462Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:919633fe66c1fd8fe0ff836dcf6d1f72fb2854e99b7b0f50e0dc5b3a5bc59ae6","observation_id":"248a95dd-3847-4ec8-91f9-a4f3c00503fe","resolution":{"observed_at":"2026-08-12T13:11:49.679033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T13:11:49.661004Z","title":"Trajectory prediction network of autonomous vehi- cles with fusion of historical interactive features,","venue":null,"work_id":"45bb6a70-f703-4ae5-8096-cd02a3bb7ed9","year":2023},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.420490Z"},"links":{"citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:96a92cf66aad4418da6afb65b501c7da35c2bd1fded10e451d2ec6750e0b8714","observation_id":"b3ee1992-5314-4ce5-b68a-af609d5a3107","resolution":{"observed_at":"2026-08-12T13:11:49.665998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"cited_work":{"arxiv_id":"2411.16457","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.16457","snapshot_observed_at":"2026-08-12T13:11:49.457598Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","venue":"cs.RO","work_id":"f2c2d052-b834-461a-820a-dea69f429694","year":2024},"citing_paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-12T13:11:49.423780Z"},"links":{"cited_paper":"/paper/2411.16457","citing_paper":"/paper/2411.16457"},"observation_digest":"sha256:7e7615f8dc1096b0f2761e5be8fb969c10da965f39899aa4533f2eec9259c393","observation_id":"008b2a9e-db5f-43e9-86d8-63602a8d6323","resolution":{"observed_at":"2026-08-12T13:11:49.464108Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.16457","last_updated":"2024-11-25T15:03:44Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-12T13:03:22.696416Z","submitted_at":"2024-11-25T15:03:44Z","title":"Characterized Diffusion Networks for Enhanced Autonomous Driving Trajectory Prediction"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":7,"verified_exact":3,"verified_fuzzy":45},"total_outbound_references":56},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 1 inbound Pith citation observation for arXiv:2411.16457."}