{"as_of":"2026-08-10T01:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:aab1d6ec50034e980e96a39d01c4c3496c2ea4967d3f838b4211fdcbee013729","coverage":[{"denominator":36,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":36,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T11:14:08.636486Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:36:04.116862Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T23:59:06.438624Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.02773","snapshot_observed_at":"2026-08-07T04:36:04.116862Z","title":"Christensen, Marcell Vazquez-Chanlatte, and Chikao Tsuchiya","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.10317","last_updated":"2025-06-20T00:26:10Z","snapshot_observed_at":"2026-08-09T15:51:07.039239Z","submitted_at":"2025-06-12T03:02:01Z","title":"Using Language and Road Manuals to Inform Map Reconstruction for Autonomous Driving","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:36:04.116862Z"},"links":{"cited_paper":"/paper/2502.02773","citing_paper":"/paper/2506.10317"},"observation_digest":"sha256:89a8d6c4bb14a27cd3bd8bc1885ee8c573bda27413e6869ba5b0a2ae59fd9d5b","observation_id":"6c4563bd-8142-4d3f-b765-63669ae98b23","resolution":{"observed_at":"2026-08-07T04:36:04.116862Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"cited_work":{"arxiv_id":"2502.02773","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.02773","snapshot_observed_at":"2026-07-03T23:59:06.438624Z","title":"Sd++: Enhancing standard definition maps by incorporating road knowledge using llms.arXiv preprint arXiv:2502.02773, 2025","venue":null,"work_id":"d78cbd09-80c2-4e28-9723-ef3f2cdcc085","year":2025},"citing_paper":{"arxiv_id":"2606.20725","last_updated":"2026-06-17T00:05:43Z","snapshot_observed_at":"2026-08-08T08:18:38.740715Z","submitted_at":"2026-06-17T00:05:43Z","title":"D2HDMap: Non-visible Driveline Map Prior for Online Vectorized HD Map Prediction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-26T21:37:28.212383Z"},"links":{"cited_paper":"/paper/2502.02773","citing_paper":"/paper/2606.20725"},"observation_digest":"sha256:0a1779322918a9540d9f2c4252c833a59171405f64a7ad2a1f984be62e426377","observation_id":"3113e623-4aa6-41fb-b829-26266adc9171","resolution":{"observed_at":"2026-07-03T23:59:06.441085Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.02773/citation-record","integrity":"/paper/2502.02773/integrity","json":"/paper/2502.02773/citation-record.json","paper":"/paper/2502.02773"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.386725Z","title":null,"venue":null,"work_id":"01ee7a94-d4a8-41ae-93ac-cc3e8aa6c13a","year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.452074Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:d1492da6e048578895e84ae886f1a1c4515a3eab2a09948fadee75dc7edbecec","observation_id":"b04897f6-2304-435f-81c4-023b5fa535df","resolution":{"observed_at":"2026-08-09T11:14:09.391618Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.06307","last_updated":"2022-03-18T08:15:56Z","snapshot_observed_at":"2026-08-05T09:30:42.951825Z","submitted_at":"2021-07-13T18:06:46Z","title":"HDMapNet: An Online HD Map Construction and Evaluation Framework","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.06307","snapshot_observed_at":"2026-08-09T11:14:08.457725Z","title":"HDMapNet: An online hd map construction and evaluation framework","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.457725Z"},"links":{"cited_paper":"/paper/2107.06307","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:fe354d1c8e8053ad7edce46cdafd6f291ffa79430fa9e5173a6298e4331ff07d","observation_id":"0799bcbd-ff16-4846-8667-dac9b7b48809","resolution":{"observed_at":"2026-08-09T11:14:08.457725Z","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":"2026-08-09T11:14:09.371194Z","title":"MapTR: Structured modeling and learning for online vectorized hd map construction","venue":null,"work_id":"c8150756-b193-4219-b8e7-ed67d9e965b9","year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.463171Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:c824d54865ec23e68f5587bd7a946d8d7807ca20f2e89ff1dc07632858528638","observation_id":"167a140a-3893-4901-a0e3-ba0a5826d193","resolution":{"observed_at":"2026-08-09T11:14:09.376187Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.05277","last_updated":"2023-08-28T10:51:09Z","snapshot_observed_at":"2026-07-06T15:14:28.574778Z","submitted_at":"2023-04-11T15:23:29Z","title":"Graph-based Topology Reasoning for Driving Scenes","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.05277","snapshot_observed_at":"2026-08-09T11:14:08.468299Z","title":"Graph-based topology reasoning for driving scenes","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.468299Z"},"links":{"cited_paper":"/paper/2304.05277","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:b7a0721aa64a8dd60eeda0d3326517254733ed27f25dfbdf91988eb62a228b5b","observation_id":"89a1d4c0-ef23-47e8-aa7f-287393d004ea","resolution":{"observed_at":"2026-08-09T11:14:08.468299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.00250","last_updated":"2024-04-30T23:45:16Z","snapshot_observed_at":"2026-08-09T15:50:51.849274Z","submitted_at":"2024-04-30T23:45:16Z","title":"SemVecNet: Generalizable Vector Map Generation for Arbitrary Sensor Configurations","version":1},"cited_work":{"arxiv_id":"2405.00250","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.00250","snapshot_observed_at":"2026-08-09T11:14:09.045523Z","title":"SemVecNet: Generalizable Vector Map Generation for Arbitrary Sensor Configurations","venue":"cs.CV","work_id":"cc12145e-4c0e-4e47-bd16-e0a312ced262","year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.474239Z"},"links":{"cited_paper":"/paper/2405.00250","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:f3bca335fcd38e1d5e5b71c956681ee5a968773efc21ef70161c6ad4dcc29b12","observation_id":"147960da-0104-417a-aebf-512fc8c09fc0","resolution":{"observed_at":"2026-08-09T11:14:09.050888Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.355527Z","title":"Planet dump retrieved from https://planet.osm.org , 2017","venue":null,"work_id":"29bfb9c9-9530-439b-ba45-b02749a427ec","year":2017},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.479716Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:d3aea709e5064026410b2478469335bbe677591a081d23bf6458cd70f47aba0b","observation_id":"93c4f4c3-f9fe-42db-93c6-27c9debe56ff","resolution":{"observed_at":"2026-08-09T11:14:09.360389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.339762Z","title":"How good is volunteered geographical infor- mation? a comparative study of openstreetmap and ordnance sur- vey datasets","venue":null,"work_id":"dd2bcd59-1701-4540-85a1-11581b7d3efc","year":2010},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.486003Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:d2965884c5a496924580eac009cccdfeb82eee694815ac8b0d1f38925ad741a5","observation_id":"e2ee2149-1071-4014-a5ad-9031abc37e96","resolution":{"observed_at":"2026-08-09T11:14:09.344510Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.04079","last_updated":"2023-11-07T15:42:22Z","snapshot_observed_at":"2026-07-06T16:44:15.428223Z","submitted_at":"2023-11-07T15:42:22Z","title":"Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.04079","snapshot_observed_at":"2026-08-09T11:14:08.490962Z","title":"Augmenting lane percep- tion and topology understanding with standard definition navigation maps","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.490962Z"},"links":{"cited_paper":"/paper/2311.04079","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:3f58430dd295311bcc50c533bdee3a8b0c89ecf951767f67ca57e59668ce0cab","observation_id":"85824819-3bbf-4588-9599-67c179f60ee3","resolution":{"observed_at":"2026-08-09T11:14:08.490962Z","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":"2026-08-09T11:14:09.325502Z","title":"Christensen, and Liu Ren","venue":null,"work_id":"db6f9595-762d-4a08-9e56-6a2b990e432c","year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.496432Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:96057fcddbbae1ba450b739bd876e73d0dd25cffdac77e138b2bd7f75651ab85","observation_id":"58a85c1c-21e8-4a52-a311-e321473b30a0","resolution":{"observed_at":"2026-08-09T11:14:09.329633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.312088Z","title":"Department of Transportation","venue":null,"work_id":"a6153ad8-7dcc-4916-8547-16a004a932df","year":2020},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.501529Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:81d445d719f9d3b2bfc84d5dc41ccfd6d22acc9c4a737d64aceb2b236e7db400","observation_id":"0dda9219-a7bc-494f-a1ba-68c26cddf5ef","resolution":{"observed_at":"2026-08-09T11:14:09.316168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.296627Z","title":"Automatic construction of lane-level HD maps for urban scenes","venue":null,"work_id":"fe77f536-68f5-49c7-b770-5fcb1d7bada7","year":2021},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.506823Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:c10ce7d1407eb3ee53b6dcf79e8898466e5cb9a10cbc6697772dfa5b6189e316","observation_id":"1054e523-155b-4eb5-95b2-2bc8479c536d","resolution":{"observed_at":"2026-08-09T11:14:09.301787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01412","last_updated":"2024-11-09T02:41:02Z","snapshot_observed_at":"2026-08-09T15:49:58.636852Z","submitted_at":"2023-10-02T17:59:52Z","title":"DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01412","snapshot_observed_at":"2026-08-09T11:14:08.511699Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.511699Z"},"links":{"cited_paper":"/paper/2310.01412","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:9ca32b79db72165bb14be3faabc7ce90a645b7e361d9a01abf322106beaf73d0","observation_id":"b1454c1a-c2c9-43c7-a038-3c211e209914","resolution":{"observed_at":"2026-08-09T11:14:08.511699Z","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":"2026-08-09T11:14:09.281051Z","title":"Lmdrive: Closed-loop end- to-end driving with large language models","venue":null,"work_id":"05e7b228-10bb-47f6-a409-e2aa7cc4994e","year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.516953Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:3601bfa01dcda939de78f7f39ff9988af5fe6abf4a8dd598f5cc029b4eae12bd","observation_id":"15cf3927-68a6-46b1-8be0-694ee1947177","resolution":{"observed_at":"2026-08-09T11:14:09.285780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11307","last_updated":"2023-09-11T19:13:00Z","snapshot_observed_at":"2026-08-09T15:50:48.602539Z","submitted_at":"2023-05-18T21:09:17Z","title":"Semantic Anomaly Detection with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11307","snapshot_observed_at":"2026-08-09T11:14:08.521726Z","title":"Semantic anomaly detection with large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.521726Z"},"links":{"cited_paper":"/paper/2305.11307","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:a31662bf8cb87d3a9dca38401356f3507db93e1374831e7a863ce9924e4a90fa","observation_id":"e8dd82d9-88c8-4b0b-aa97-164e24a96558","resolution":{"observed_at":"2026-08-09T11:14:08.521726Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05186","last_updated":"2025-03-24T07:07:59Z","snapshot_observed_at":"2026-08-07T06:42:30.664178Z","submitted_at":"2023-09-11T01:24:13Z","title":"HiLM-D: Enhancing MLLMs with Multi-Scale High-Resolution Details for Autonomous Driving","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05186","snapshot_observed_at":"2026-08-09T11:14:08.526943Z","title":"HiLM-D: Towards high-resolution understanding in multimodal large language models for autonomous driving","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.526943Z"},"links":{"cited_paper":"/paper/2309.05186","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:55e010a514613a21130a3337376ea266acecedc8a20e110d26d51cbe64ac41de","observation_id":"a4bfc406-70a5-41a0-bdb9-7887a2762fd4","resolution":{"observed_at":"2026-08-09T11:14:08.526943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.11057","last_updated":"2024-07-30T02:35:52Z","snapshot_observed_at":"2026-08-01T15:12:34.494772Z","submitted_at":"2024-03-17T02:06:49Z","title":"Large Language Models Powered Context-aware Motion Prediction in Autonomous Driving","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.11057","snapshot_observed_at":"2026-08-09T11:14:08.532966Z","title":"Large language models powered context-aware motion prediction in autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.532966Z"},"links":{"cited_paper":"/paper/2403.11057","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:40a9b1d2aad95efae9cdc31c5d3ba5462f95c875f9fa84025c275f0c7bba9318","observation_id":"ddf0976d-aa92-49b7-ac46-f3320fa12289","resolution":{"observed_at":"2026-08-09T11:14:08.532966Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.16118","last_updated":"2023-07-30T03:50:52Z","snapshot_observed_at":"2026-07-06T16:00:16.896971Z","submitted_at":"2023-07-30T03:50:52Z","title":"MTD-GPT: A Multi-Task Decision-Making GPT Model for Autonomous Driving at Unsignalized Intersections","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.16118","snapshot_observed_at":"2026-08-09T11:14:08.538343Z","title":"MTD- GPT: A multi-task decision-making gpt model for autonomous driving at unsignalized intersections","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.538343Z"},"links":{"cited_paper":"/paper/2307.16118","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:9852bb274b426b7bc378f33667396bff4f4800451b5af50c085e2b51770dd443","observation_id":"bbd08b9c-efc5-44e2-964a-31a6b93900ee","resolution":{"observed_at":"2026-08-09T11:14:08.538343Z","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":"2026-08-09T11:14:08.543550Z","title":"LC-LLM: Explainable lane-change intention and trajectory predictions with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.543550Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:483c826961f14bac5c4d50fb77dca3dbf246aea1f11b61db35990563bd6cc60b","observation_id":"43cd21e1-02ae-49e1-834e-c8b1e07d43e7","resolution":{"observed_at":"2026-08-09T11:14:08.543550Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01587","last_updated":"2024-06-04T07:48:11Z","snapshot_observed_at":"2026-08-05T10:39:42.651286Z","submitted_at":"2024-06-03T17:59:27Z","title":"PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01587","snapshot_observed_at":"2026-08-09T11:14:08.548427Z","title":"PlanAgent: A multi-modal large language agent for closed-loop vehicle motion planning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.548427Z"},"links":{"cited_paper":"/paper/2406.01587","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:e27810de753a89fe7d282cd7b7ecf15f79e58a43978dfe55430f9e1f8bb7b5f3","observation_id":"d9c70daf-eb7c-4f5b-9d7c-ffa56cec6fff","resolution":{"observed_at":"2026-08-09T11:14:08.548427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03641","last_updated":"2024-01-08T03:06:02Z","snapshot_observed_at":"2026-07-06T17:12:34.262376Z","submitted_at":"2024-01-08T03:06:02Z","title":"DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03641","snapshot_observed_at":"2026-08-09T11:14:08.553785Z","title":"DME-Driver: Integrating human decision logic and 3D scene percep- tion in autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.553785Z"},"links":{"cited_paper":"/paper/2401.03641","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:06e217a9325d574c4985bf9ee57f4b54f3b726984a1fbe9b5a686aadfc7b5ba2","observation_id":"8bd92189-b384-4552-b132-e0a3f765ab03","resolution":{"observed_at":"2026-08-09T11:14:08.553785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10813","last_updated":"2021-11-21T13:04:48Z","snapshot_observed_at":"2026-07-06T12:10:34.925614Z","submitted_at":"2021-11-21T13:04:48Z","title":"Experience-Enhanced Learning: One Size Still does not Fit All in Automatic Database","version":1},"cited_work":{"arxiv_id":"2111.10813","doi":null,"metadata_source":"pith","pith_arxiv_id":"2111.10813","snapshot_observed_at":"2026-08-09T11:14:08.723680Z","title":"Experience-Enhanced Learning: One Size Still does not Fit All in Automatic Database","venue":"cs.DB","work_id":"39923e7b-35fa-4c30-b165-52f8484bb36d","year":2021},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.560848Z"},"links":{"cited_paper":"/paper/2111.10813","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:28e94c82b58f6a0c542b77bbb094392285afb5dbfe98a234f5496cb65ae99db5","observation_id":"7b59f974-7bdf-42c4-9652-722ec823b6cd","resolution":{"observed_at":"2026-08-09T11:14:08.731000Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02251","last_updated":"2023-11-14T14:46:05Z","snapshot_observed_at":"2026-07-06T16:27:15.027202Z","submitted_at":"2023-10-03T17:53:51Z","title":"Talk2BEV: Language-enhanced Bird's-eye View Maps for Autonomous Driving","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02251","snapshot_observed_at":"2026-08-09T11:14:08.566354Z","title":"Singh, Siddharth Srivastava, Krishna Murthy Jatavallabhula, and K","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.566354Z"},"links":{"cited_paper":"/paper/2310.02251","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:4172af39536a538fe72afc39125d600905bed5f5c8065d9075bae12b713766c3","observation_id":"62006ed6-2481-446e-9e71-85b6b8096197","resolution":{"observed_at":"2026-08-09T11:14:08.566354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-09T11:14:08.571690Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.571690Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:e65fcda20a2f1185b4c068710e317932280f9a1d5ab6a07ad2f8b87d60366e69","observation_id":"e4ed9633-9f7a-4e95-bc7a-3e31369a664e","resolution":{"observed_at":"2026-08-09T11:14:08.571690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.13971","last_updated":"2023-03-24T12:45:42Z","snapshot_observed_at":"2026-07-06T15:07:37.299096Z","submitted_at":"2023-03-24T12:45:42Z","title":"Optimal Transport for Offline Imitation Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.13971","snapshot_observed_at":"2026-08-09T11:14:08.576676Z","title":"LLaMA: Open and Efficient Foundation Language Models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.576676Z"},"links":{"cited_paper":"/paper/2303.13971","citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:28452381427ed56714c90bbf89324cac5070a4ece0e2a727c675d29815505d46","observation_id":"18b8e24a-b378-4875-86bc-334f59871b13","resolution":{"observed_at":"2026-08-09T11:14:08.576676Z","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":"2026-08-09T11:14:09.265586Z","title":"A/B-street","venue":null,"work_id":"d52bbab7-a64a-46f4-8462-bb16bf6f441c","year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.581849Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:ec61fb9b404a3a22edc951244ac385b2a6c49c8f7a685940b7d7b706d0bef7ab","observation_id":"47991a16-30a7-48cf-8cc4-98f1876571d6","resolution":{"observed_at":"2026-08-09T11:14:09.270347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.249819Z","title":"Argoverse 2: Next generation datasets for self-driving perception and forecasting","venue":null,"work_id":"d36ebd51-9467-42cb-902f-165243d96c41","year":2021},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.586639Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:fffe0179a169525aebafc02249804f25c2b368f4d524a2c557ef83f1e0e6ffdb","observation_id":"5ba602ba-5213-4f63-87d5-7b05aef77475","resolution":{"observed_at":"2026-08-09T11:14:09.254826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.233181Z","title":"Osmium: A c++ library for work- ing with openstreetmap data","venue":null,"work_id":"19c5c9a4-94b0-4ab1-91e3-cfadc53086b9","year":2025},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.592023Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:7cc127a157e881c6a918f41c04d8b5eeebf4994251ccda54955ed8c05cdbfe91","observation_id":"46116a7d-534f-428a-9cd6-6828fa92bf3e","resolution":{"observed_at":"2026-08-09T11:14:09.238643Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.216466Z","title":"OSMfilter","venue":null,"work_id":"c0e29163-c071-48d7-8b22-58bd7b1047f8","year":2024},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.596718Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:557b07bff56f0679d8f31d8e5becdbeff880ef853ad14ce71af4519d3c38eae9","observation_id":"1bb79a5e-c13f-4ccb-8c54-d40bf1655964","resolution":{"observed_at":"2026-08-09T11:14:09.221402Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.200576Z","title":"LangChain","venue":null,"work_id":"e5a9874a-8cac-408b-8627-3b782461d1f0","year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.602019Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:b9a082b5fd9e1dd649f84452e0c5dfe4a5ab2cb21efbfece2c058e3f724d9182","observation_id":"0ae88e28-95ef-42f1-b43a-8c9f401f8211","resolution":{"observed_at":"2026-08-09T11:14:09.205655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.185139Z","title":"Pypdfloader","venue":null,"work_id":"bab97a08-e828-4a42-8990-30b29601eb3f","year":2023},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.606751Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:af3394a7df752424e9dcbf6177fd3df74e077d2a3530fcebeae23d915bae5f6a","observation_id":"9f9ebf03-5ee4-4752-8bf8-26e777695e45","resolution":{"observed_at":"2026-08-09T11:14:09.190088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.167567Z","title":null,"venue":null,"work_id":"09db18a3-35e3-4cc1-88b1-3bb74ff624a9","year":1977},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.611492Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:82ba088ac85caec3fa3e4aed4daac0f71d8c6ce5ca8cd263172794d74462d4b1","observation_id":"7f2457ea-6e82-4f34-9a06-cca747b9927f","resolution":{"observed_at":"2026-08-09T11:14:09.173786Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.151441Z","title":"Prompt programming for large language models: Beyond the few-shot paradigm, 2021","venue":null,"work_id":"a263f202-633c-4bf7-a880-faaeb1fa8ffb","year":2021},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.616524Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:5ed6fc13191329e0ea596b1481c3d028c7441dd53af37084f12cb2b7f3c37776","observation_id":"1191447f-72a3-4633-a257-722cc37d17fa","resolution":{"observed_at":"2026-08-09T11:14:09.156609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:08.621468Z","title":"Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.621468Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:00b36ff6234fea8d4e38b8c1e06feebfaa22760ecac3a5161538fbbd7bc57290","observation_id":"cd541071-2686-4277-a83d-c9d567dfcc2f","resolution":{"observed_at":"2026-08-09T11:14:08.621468Z","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":"2026-08-09T11:14:09.126339Z","title":"Google Earth Satellite Image","venue":null,"work_id":"c27005a6-a40d-4f0b-8966-1afefce8e3ee","year":null},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.626108Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:8bb85b8ded5a785d23363df96f1c07a0be0adf3759d4c9aa30160534089e26d0","observation_id":"3b5d1efc-f880-4e27-b4b2-1eb57ab6e8c8","resolution":{"observed_at":"2026-08-09T11:14:09.130911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.111212Z","title":null,"venue":null,"work_id":"59039259-c149-46bb-98c3-e2b56c99c3b1","year":1947},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.631122Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:c6b1bfda24a2cbe5935a003eb6ad572c3aa54ddf8939d579f373da7d8a1ce8bd","observation_id":"b24a9c11-b0ec-45fe-8ecf-6ee7335133f8","resolution":{"observed_at":"2026-08-09T11:14:09.115881Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T11:14:09.095282Z","title":"Caltrain current projects","venue":null,"work_id":"693e6a4d-0cd9-4347-8f90-a199c75e8748","year":2025},"citing_paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-09T11:14:08.636486Z"},"links":{"citing_paper":"/paper/2502.02773"},"observation_digest":"sha256:2da2c771dc652f4f91af6c0b21ba8cc5b006c147f0bae2f1fa85137927b567a9","observation_id":"2833ae6e-0af3-4033-b58a-fd1dc6ba8dd7","resolution":{"observed_at":"2026-08-09T11:14:09.100422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.02773","last_updated":"2025-06-20T00:43:05Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-09T15:51:07.640732Z","submitted_at":"2025-02-04T23:35:51Z","title":"SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs"},"reference_resolution":{"displayed":36,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":2,"verified_fuzzy":16},"total_outbound_references":36},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:2502.02773."}