{"as_of":"2026-08-07T16:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d2f0ba7684952221348ea319bca5a5d6a29325fa2c061756e77d256a49d26c3e","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:24:51.445863Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.08903/citation-record","integrity":"/paper/2507.08903/integrity","json":"/paper/2507.08903/citation-record.json","paper":"/paper/2507.08903"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:24:53.611208Z","title":"Hdmapnet: An online hd map construction and evaluation framework,","venue":null,"work_id":"788bd66b-e817-4ae4-b9ce-bf762a9ebb61","year":2022},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:26.056454Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:e3c8c17213d2d558d2f98c496cac0c4b4763cebf90ae04326f2d373707f96369","observation_id":"57b81c6b-8f6d-4a12-9af1-ce951bc61551","resolution":{"observed_at":"2026-08-06T18:24:53.657719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.05736","last_updated":"2024-10-25T09:28:05Z","snapshot_observed_at":"2026-07-06T16:04:58.235073Z","submitted_at":"2023-08-10T17:56:53Z","title":"MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.05736","snapshot_observed_at":"2026-08-06T18:24:26.077528Z","title":"Maptrv2: An end-to-end framework for online vectorized hd map construction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:26.077528Z"},"links":{"cited_paper":"/paper/2308.05736","citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:92dd78f3d465e91d59b53d965886d9102905fcb5e9883223f1327d0a07f45799","observation_id":"a9a67dac-b691-4ee8-8aae-8267e8b2f11a","resolution":{"observed_at":"2026-08-06T18:24:26.077528Z","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":"2026-08-06T18:24:26.206822Z","title":"Mgmap: Mask-guided learning for online vectorized hd map construction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:26.206822Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:d1bae4bb79a9d5d6c2da543b8d59ac5bc09ea73e34047fa901fef02b824f393b","observation_id":"41d3311b-95c3-4434-8693-e22acc97dfd1","resolution":{"observed_at":"2026-08-06T18:24:26.206822Z","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":"2026-08-06T18:24:53.521677Z","title":"V2x-seq: A large-scale sequential dataset for vehicle-infrastructure cooperative perception and forecasting,","venue":null,"work_id":"796f7a1b-ff03-464d-aa6b-3f3afa9b680e","year":2023},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:26.297230Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:0a7880d578affe138bf324f4a5bf50a737464c068cca51fcc463a02ed569b827","observation_id":"d0269ce6-13ad-4dce-84e1-fb7642107ba7","resolution":{"observed_at":"2026-08-06T18:24:53.557738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:53.418482Z","title":"Design and implementation of edge-fog-cloud system through hd map generation from lidar data of autonomous vehicles,","venue":null,"work_id":"f05faca8-6d25-46a3-884d-baea2edd3d58","year":2020},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:26.443079Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:5c513be3adc736328c5d847c4b4d33ae659a6810ae128bdcad737a08995537ed","observation_id":"896fccc8-332a-4772-8634-f7cdbbdc50aa","resolution":{"observed_at":"2026-08-06T18:24:53.463787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:53.269945Z","title":"Pointpillars: Fast encoders for object detection from point clouds,","venue":null,"work_id":"31e9f2f6-cb95-414a-a527-5085cb0656c8","year":2019},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:26.520688Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:c99d3bd2b4de91118a85a8bbf3af250900a75b471e8f7368c13a5c5b0498a827","observation_id":"b55f5481-86c2-4ca5-a393-c22aac6fc126","resolution":{"observed_at":"2026-08-06T18:24:53.364306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:53.094613Z","title":"Bevfusion: A simple and robust lidar-camera fusion framework,","venue":null,"work_id":"e9ff1f31-aaf8-4eac-b29d-dd72788dbad7","year":2022},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:26.583333Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:79f6b26215355c796eed22c0e50081adf3fcc8bce0bd72ef83624259b77f83c6","observation_id":"b7806bf7-a876-4b67-af7e-d5a5872e2d9d","resolution":{"observed_at":"2026-08-06T18:24:53.167091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:53.020583Z","title":"Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,","venue":null,"work_id":"3bc3aa8b-45df-4170-b0cc-547abf473654","year":2020},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.359477Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:50d75d78c81dd9b724610ca9d7dba9f32885921c9b5ddf5850bf939d9ba561ec","observation_id":"674819aa-0ab0-4d30-8da0-4627cd898ece","resolution":{"observed_at":"2026-08-06T18:24:53.041741Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:50.456597Z","title":"Second: Sparsely embedded convolutional detection,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.456597Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:cc08dd4d4ba61b5a610d5dbb1ba2751ef77892ac7c55ab6708a3e21af21bcb4f","observation_id":"6d1df1da-06ab-44cd-9133-f6bcf0325db0","resolution":{"observed_at":"2026-08-06T18:24:50.456597Z","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":"2026-08-06T18:24:52.921440Z","title":"Superfusion: Multilevel lidar-camera fusion for long- range hd map generation,","venue":null,"work_id":"63fe67d1-09eb-4ce0-9c47-53c1c9e9da34","year":2024},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.498116Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:71401c95e3eb6ed923ece7f55374700c838912d80d36602e899d49513859b823","observation_id":"e25fdb6a-2037-4161-9947-febdccd5b2fb","resolution":{"observed_at":"2026-08-06T18:24:52.963299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:52.837408Z","title":"V2x-vit: Vehicle-to-everything cooperative perception with vision transformer,","venue":null,"work_id":"bd677d83-edfa-4bb6-9b3e-224dab44321d","year":2022},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.641296Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:1945aec8e2797ca4bd2c2a19851b694217641aa8bad0dbf7accd761875166e00","observation_id":"7f350c49-57b5-4c9d-a4ba-7a988f3c23cc","resolution":{"observed_at":"2026-08-06T18:24:52.873023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:52.720007Z","title":"Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task,","venue":null,"work_id":"e81c56a8-3c54-4fea-a37f-bf3a714770b2","year":2022},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.721459Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:19315b840394c39798cc739a79c6fbb07fec0f632d75978119a044f746559620","observation_id":"87e0189b-6f62-4634-9f94-ac4e33a02456","resolution":{"observed_at":"2026-08-06T18:24:52.770414Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:52.586687Z","title":"Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection,","venue":null,"work_id":"e354f06e-245f-4689-ac8a-7c30d399399b","year":2022},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.780576Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:a59a359b8ab372327de613dc24fb4b2ff1708816d6a7b53786eb49dee98ee894","observation_id":"045c4b44-7f48-4cc4-94be-35680bdbe648","resolution":{"observed_at":"2026-08-06T18:24:52.652573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:52.450776Z","title":"Tumtraf v2x cooperative perception dataset,","venue":null,"work_id":"5eb97a83-9e21-4bea-9759-049d845d86d6","year":2024},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.875455Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:7c92a10d3a0cee3e2057581533094dc9091df18e50201a0010864284fb84bd64","observation_id":"c837b143-21f0-4305-8c65-a3ee1959c8ef","resolution":{"observed_at":"2026-08-06T18:24:52.520925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:52.169773Z","title":"Vi-map: Infrastructure-assisted real-time hd mapping for autonomous driving,","venue":null,"work_id":"59f8f57a-843d-490d-a5aa-aa2fe4d5ef0c","year":2023},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:50.966862Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:98f6364ab889eea2e298af44f78142df2704fc045c0036f07d5f2974d588f21f","observation_id":"b246d3e9-9e32-42ce-aaec-021f269f21f8","resolution":{"observed_at":"2026-08-06T18:24:52.339850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:51.055662Z","title":"Carla: An open urban driving simulator,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:51.055662Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:42f614597c01a1462d5cf653ff6087cb8490e7aeaf265a91bd47d82b73ab368b","observation_id":"77c874ee-b547-4173-bc96-2ed542be0af7","resolution":{"observed_at":"2026-08-06T18:24:51.055662Z","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":"2026-08-06T18:24:51.964890Z","title":"Denoising of a multi- station point cloud and 3d modeling accuracy for substation equipment based on statistical outlier removal,","venue":null,"work_id":"79c159ce-0035-4366-903a-1ddcbe37c043","year":2020},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:51.097534Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:fd5ff1cb2799877c2be19a70c805fed3e67a80b737ed721dba8e18fa31c62691","observation_id":"12a86c65-1201-4a2f-9579-59ae405a4d46","resolution":{"observed_at":"2026-08-06T18:24:52.065409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:51.884111Z","title":"Three-dimensional alpha shapes,","venue":null,"work_id":"1d4297da-db60-478f-a076-30133158bbdb","year":1994},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:51.180532Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:d7fc69eb0999abf75dde71a46e95e78fbbc0904a896d20aa474668a0d71fcdde","observation_id":"ff42cde6-160b-4dba-b54e-039f0988ed64","resolution":{"observed_at":"2026-08-06T18:24:51.914753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:51.780890Z","title":"Least-squares fitting of a straight line,","venue":null,"work_id":"2a24256d-afcc-4bda-9fa8-32dce6f251e1","year":1966},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:51.254048Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:2457e83c518faaaad9adf9649975e06405f25e7ddb7927b8d368bc0ab0cf9bfc","observation_id":"5ad0f6bb-566b-43c4-b9d4-f2d98ddd634b","resolution":{"observed_at":"2026-08-06T18:24:51.825713Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:51.328844Z","title":"U-net: Convolutional networks for biomedical image segmentation,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:51.328844Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:cbde7d47c4055b520646a25d163b08bd0d28f724e213b02903043abc4d54dc2b","observation_id":"1b91af7e-3044-4633-a8bc-6d79fdd2dc21","resolution":{"observed_at":"2026-08-06T18:24:51.328844Z","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":"2026-08-06T18:24:51.650147Z","title":"Pidnet: A real-time semantic segmentation network inspired by pid controllers,","venue":null,"work_id":"f753cc60-3f8b-407e-a7d4-468139553e4f","year":2023},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:51.399138Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:132568adb1846338acb205b258ab1ac4192cb23d63c76ae1ba15243255deae1b","observation_id":"f26aeba6-f6b8-4a64-a31c-69b7c1313734","resolution":{"observed_at":"2026-08-06T18:24:51.712347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:24:51.537010Z","title":"Vision transformer adapter for dense predictions,","venue":null,"work_id":"f7edf798-36cb-42f5-982e-d4fe7456e138","year":null},"citing_paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T18:24:51.445863Z"},"links":{"citing_paper":"/paper/2507.08903"},"observation_digest":"sha256:bf3c2555942988966633116bf8808bb38a2e7b3bc4bc9d0c2c011f172276cfba","observation_id":"2a6c48d3-ffa3-4088-b46b-8b6a9aedeaa5","resolution":{"observed_at":"2026-08-06T18:24:51.594130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.08903","last_updated":"2025-07-11T08:45:56Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-06T18:16:56.713927Z","submitted_at":"2025-07-11T08:45:56Z","title":"Multimodal HD Mapping for Intersections by Intelligent Roadside Units"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":0,"verified_fuzzy":17},"total_outbound_references":22},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2507.08903."}