{"as_of":"2026-08-14T17:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b674151f22afa2492586728c127bd095b13b65477b3a81e620e1970cfc772b5d","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T20:30:32.549046Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2412.05717/citation-record","integrity":"/paper/2412.05717/integrity","json":"/paper/2412.05717/citation-record.json","paper":"/paper/2412.05717"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T20:30:32.794723Z","title":"A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles,","venue":null,"work_id":"5561d645-1086-432f-9dad-31906ee109cd","year":2016},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.473266Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:8940e5b77ebee42f6ce52f085a88a8a5587f6c4b947bd148db3873c13ca440d9","observation_id":"7dc1bc19-381a-4a62-8b94-f44568b52858","resolution":{"observed_at":"2026-08-11T20:30:32.798805Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05449","last_updated":"2019-10-12T00:34:37Z","snapshot_observed_at":"2026-08-10T19:51:16.852667Z","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":"2026-08-11T20:30:32.476793Z","title":"Multipath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.476793Z"},"links":{"cited_paper":"/paper/1910.05449","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:a394ed34eaea99b729be48fe51a491899452b2b70176188f3d6ae5e88aeb7839","observation_id":"aca44c3a-0ba0-43fe-beb8-5c7df179f32a","resolution":{"observed_at":"2026-08-11T20:30:32.476793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.16927","last_updated":"2024-08-15T13:55:30Z","snapshot_observed_at":"2026-08-13T11:06:04.594746Z","submitted_at":"2023-06-29T14:17:24Z","title":"End-to-end Autonomous Driving: Challenges and Frontiers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.16927","snapshot_observed_at":"2026-08-11T20:30:32.480563Z","title":"End-to- end Autonomous Driving: Challenges and Frontiers,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.480563Z"},"links":{"cited_paper":"/paper/2306.16927","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:f2aa87a9397d74902845d39a7477501d95558a6c8117d6767e335a34a5d0c944","observation_id":"1fb84b1e-7652-433e-aae4-f70479ababca","resolution":{"observed_at":"2026-08-11T20:30:32.480563Z","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":"2026-08-11T20:30:32.785178Z","title":"Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety,","venue":null,"work_id":"df2619d7-6855-4f7b-a095-a21f90ba2e74","year":2019},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.484014Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:6ab9db109c998fc26d589254ef0395f8e2fa59f7c919bbf39bf3bffdfa326c23","observation_id":"0e0d0cb2-8754-496b-86c5-46d0c3f0924e","resolution":{"observed_at":"2026-08-11T20:30:32.789210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.776540Z","title":"A Survey on Imitation Learning Techniques for End-to-end Autonomous Vehicles,","venue":null,"work_id":"b66a9c9a-963b-4a41-9480-dcca7b155c88","year":2022},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.487438Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:31db16fe05dc07adeecf72e25fe8313dd93423a83b412cd51f16591d6662067c","observation_id":"31b6c868-817e-470e-8f1f-c9a40c3fdffe","resolution":{"observed_at":"2026-08-11T20:30:32.779695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.767599Z","title":"Imitation is not enough: Robustifying imitation with reinforcement learning for challenging driving scenarios,","venue":null,"work_id":"d9f4bdd3-2707-441f-9d99-0269e7c68974","year":2023},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.490667Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:895bad89e64cc6df56134a0f3e3f0cd827fcf84a97ae0f41696e6882fae5f39b","observation_id":"15269ee1-333c-45b4-b238-cfa7a1a9ff58","resolution":{"observed_at":"2026-08-11T20:30:32.770771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.09670","last_updated":"2023-03-02T07:20:08Z","snapshot_observed_at":"2026-08-14T11:02:20.639800Z","submitted_at":"2022-06-20T09:22:20Z","title":"Benchmarking Constraint Inference in Inverse Reinforcement Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.09670","snapshot_observed_at":"2026-08-11T20:30:32.493964Z","title":"Bench- marking Constraint Inference in Inverse Reinforcement Learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.493964Z"},"links":{"cited_paper":"/paper/2206.09670","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:97e732f938c332200ae9530ce0185e1403cdf286310a6c8397f967de6b67db63","observation_id":"07ccb6da-09a5-464c-afee-fb8cb5a603f5","resolution":{"observed_at":"2026-08-11T20:30:32.493964Z","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":"2026-08-11T20:30:32.758395Z","title":"How To Not Drive: Learning Driving Constraints from Demonstration,","venue":null,"work_id":"7bc9b701-f60b-48fb-9c8a-b8b042666349","year":2022},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.497219Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:ac90f9ad9600a1755f7fb830846773895f3d5674ea46b70f52fc5b58118a007d","observation_id":"6f06e6e2-659d-4323-9ae8-682116dc7852","resolution":{"observed_at":"2026-08-11T20:30:32.762229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.749925Z","title":"Learning Constraints from Demonstrations,","venue":null,"work_id":"a9cad98d-9ae7-4e69-bbb6-a19801ed7d48","year":2020},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.500197Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:4ae5d8f3ef0c5f1d745cf849b303c773848db3821366aea4be6f10937ccfbd0f","observation_id":"e2fed045-9c40-4584-a840-32bbf09dccb1","resolution":{"observed_at":"2026-08-11T20:30:32.753017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.740759Z","title":"Maximum Likelihood Constraint Infer- ence for Inverse Reinforcement Learning,","venue":null,"work_id":"a364274e-01b5-452b-bcd3-27ba7781cd70","year":2019},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.503068Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:1c75cbe584a1f2fcd04b8b3b169ce9dea89c978da78033fdee338dd3b75162e3","observation_id":"8934019a-4f09-44f4-a1e0-63458a419565","resolution":{"observed_at":"2026-08-11T20:30:32.744194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.731317Z","title":"Inverse Constrained Reinforcement Learning,","venue":null,"work_id":"7ebcd719-e157-4d79-acb9-92e3ffbf59c5","year":2021},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.506122Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:d6f71c3600593e3e96989b5fadb941cd20b29e1a22ff50d47ce9c92bf99ad8d2","observation_id":"3a814694-bc4d-4ac8-a969-f52811e3b78f","resolution":{"observed_at":"2026-08-11T20:30:32.734563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.01311","last_updated":"2023-04-27T19:26:45Z","snapshot_observed_at":"2026-08-14T11:03:04.072903Z","submitted_at":"2022-06-02T21:45:31Z","title":"Learning Soft Constraints From Constrained Expert Demonstrations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.01311","snapshot_observed_at":"2026-08-11T20:30:32.509110Z","title":"Learning Soft Constraints from Constrained Expert Demonstrations,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.509110Z"},"links":{"cited_paper":"/paper/2206.01311","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:492a12214abbdfe4c6d30c73b91ecfb9a31b99789905dd711137416a5296cb13","observation_id":"68c4d6e7-c11b-431b-9aee-3de6cf9949b7","resolution":{"observed_at":"2026-08-11T20:30:32.509110Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.00711","last_updated":"2023-09-01T19:37:36Z","snapshot_observed_at":"2026-08-13T10:22:25.136188Z","submitted_at":"2023-09-01T19:37:36Z","title":"Learning Shared Safety Constraints from Multi-task Demonstrations","version":1},"cited_work":{"arxiv_id":"2309.00711","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.00711","snapshot_observed_at":"2026-08-11T20:30:32.611287Z","title":"Learning Shared Safety Constraints from Multi-task Demonstrations","venue":"cs.LG","work_id":"36501162-7be9-4742-9b5d-dbe031c3d4f9","year":2023},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.512344Z"},"links":{"cited_paper":"/paper/2309.00711","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:4b8961adc7f362af456e71a1117542f3e65590517834dd1b76aafb6f79a70120","observation_id":"f53263ca-641b-40fa-9568-0b44e1ee7265","resolution":{"observed_at":"2026-08-11T20:30:32.615006Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04334","last_updated":"2024-01-09T03:22:16Z","snapshot_observed_at":"2026-08-14T11:01:11.657024Z","submitted_at":"2024-01-09T03:22:16Z","title":"Large Language Models for Robotics: Opportunities, Challenges, and Perspectives","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04334","snapshot_observed_at":"2026-08-11T20:30:32.515394Z","title":"Large language models for robotics: Opportunities, challenges, and perspectives,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.515394Z"},"links":{"cited_paper":"/paper/2401.04334","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:b5af1e470d9a8f84336e606cf7a4b85d09a57b12127643a37d3745490fffaec5","observation_id":"b6bf2a24-db70-4b62-84f8-b9c355608a3e","resolution":{"observed_at":"2026-08-11T20:30:32.515394Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.18209","last_updated":"2024-09-12T12:59:19Z","snapshot_observed_at":"2026-08-13T00:44:13.230103Z","submitted_at":"2024-03-27T02:41:52Z","title":"Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Driving","version":2},"cited_work":{"arxiv_id":"2403.18209","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.18209","snapshot_observed_at":"2026-08-11T20:30:32.588860Z","title":"Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Driving","venue":"cs.LG","work_id":"af19d90d-f676-4f53-ad09-8226462870e5","year":2024},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.518616Z"},"links":{"cited_paper":"/paper/2403.18209","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:467b6e76f442505985135dd684e06b6eb14b69969e6d2554891fa4f485e036c6","observation_id":"d6b3f3ec-9e75-4752-a607-6990fe2cb4b1","resolution":{"observed_at":"2026-08-11T20:30:32.592738Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.722301Z","title":"Safe autonomous driving with latent dynamics and state-wise constraints,","venue":null,"work_id":"599a9c39-b953-4633-a226-1e5e1c22c822","year":2024},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.521791Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:12449efd37630ee8d336954f34103445eed4db2bf48845980cabb749c829e870","observation_id":"d829bb1d-8072-449e-ab10-ef6761df8851","resolution":{"observed_at":"2026-08-11T20:30:32.725489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.713003Z","title":"Maximum Entropy Inverse Reinforcement Learning,","venue":null,"work_id":"0dd923ec-962f-4cf3-9987-46bd25d6b49d","year":2008},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.524761Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:fedc38a138d2b3d3bba1b1250734ec672e35f561fd50e0da6bf073dcc2e67768","observation_id":"119b1773-971f-4379-956d-2bc9357feb72","resolution":{"observed_at":"2026-08-11T20:30:32.716336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.704155Z","title":"Safetynet: Safe planning for real-world self-driving vehicles using machine- learned policies,","venue":null,"work_id":"d5f87bf4-679e-44ac-b689-750044632258","year":2022},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.527574Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:fbdccfae10d6befce9d9c1a44f6b3ed36d4a490952b30c9efce2749ffcaaff2d","observation_id":"f1461ad2-43b6-43b3-9a87-a8705c7416ea","resolution":{"observed_at":"2026-08-11T20:30:32.707388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16147","last_updated":"2024-03-02T00:37:59Z","snapshot_observed_at":"2026-08-13T11:33:19.114750Z","submitted_at":"2023-05-25T15:18:46Z","title":"Learning Safety Constraints from Demonstrations with Unknown Rewards","version":2},"cited_work":{"arxiv_id":"2305.16147","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.16147","snapshot_observed_at":"2026-08-11T20:30:32.573935Z","title":"Learning Safety Constraints from Demonstrations with Unknown Rewards","venue":"cs.LG","work_id":"c1c8406b-0e03-402b-944b-120d0aa425fc","year":2023},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.530442Z"},"links":{"cited_paper":"/paper/2305.16147","citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:8f95646d8c875d82b89457fbaa8083c96769e849ca1987bbd1f79f76bbda62e1","observation_id":"b075ff8d-a708-4139-a92d-1bc8788b23f8","resolution":{"observed_at":"2026-08-11T20:30:32.579103Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.695088Z","title":"Learning constraints on autonomous behavior from proactive feedback,","venue":null,"work_id":"0ce2b231-a9e0-40c1-8ecd-559de3d79c49","year":2023},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.533504Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:b3315e88d5635af15a62d08afb2f99f8f8f04e31ab0cb655636ae6de5982bd53","observation_id":"946a6a95-4c0c-455f-af21-245431c8d0fa","resolution":{"observed_at":"2026-08-11T20:30:32.698279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T20:30:32.536540Z","title":"An Environment for Autonomous Driving Decision- Making,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.536540Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:a633b0673dd00db9a812d48fc5693fbf3aaad185862dd6ad7f873f93b282acf2","observation_id":"9a1325b1-baf0-4ff0-b863-85d83ad24422","resolution":{"observed_at":"2026-08-11T20:30:32.536540Z","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":"2026-08-11T20:30:32.680604Z","title":"The Ind Dataset: A Drone Dataset of Naturalistic Road User Tra- jectories at German Intersections,","venue":null,"work_id":"281da33e-59f9-45df-b02f-635703aadfa1","year":2020},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.539568Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:cfb052dad944fe3f376170b1ad7904abccf90c750e5b594e1c5158a2c1029add","observation_id":"f3619bf3-c8af-4074-8393-7b2739119b68","resolution":{"observed_at":"2026-08-11T20:30:32.683765Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.671226Z","title":"Tnt: Target-Driven Trajectory Prediction,","venue":null,"work_id":"4417ef3e-e360-4907-9508-4e3c233e1527","year":2021},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.542656Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:986fe054bbaeec3e1a0294482cdc61946208e9fb3cafd1a077e7d8323e9a6125","observation_id":"71f0b2d7-2f95-43be-8154-435c5c8f5ffc","resolution":{"observed_at":"2026-08-11T20:30:32.675004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.661448Z","title":"Vectornet: Encoding HD Maps and Agent Dynamics from Vectorized Representation,","venue":null,"work_id":"8f69f92d-fae3-4c82-8ba2-8c411a5ae5c7","year":2020},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.545470Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:7c91cf21addd84889aa77bab379fd588edbe1f6c1690942fca5bfd0603795697","observation_id":"b65bdfb6-a5e1-4f4c-a317-0c42f196ecd1","resolution":{"observed_at":"2026-08-11T20:30:32.665436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-11T20:30:32.652617Z","title":"Safety-Critical Scenario Generation Via Reinforcement Learning Based Editing,","venue":null,"work_id":"25811272-b723-45d5-9887-4488d53d2597","year":2024},"citing_paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T20:30:32.549046Z"},"links":{"citing_paper":"/paper/2412.05717"},"observation_digest":"sha256:8fe181bb3205a3d5cf886c7cdd263f5bc427008ca2d6961d31d67e5582bc1bc6","observation_id":"4601a059-e05c-4597-bd27-ffdb184e3168","resolution":{"observed_at":"2026-08-11T20:30:32.655796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.05717","last_updated":"2024-12-07T18:29:28Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-14T11:01:31.073900Z","submitted_at":"2024-12-07T18:29:28Z","title":"Learning Soft Driving Constraints from Vectorized Scene Embeddings while Imitating Expert Trajectories"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":3,"verified_fuzzy":16},"total_outbound_references":25},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2412.05717."}