{"as_of":"2026-08-01T11:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:229af48aa1fd7b64598246551f56c6a35cb9087796bd88ff0cc6155c26a5edae","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-01T06:32:01.292127+00:00","state":"measured"},{"denominator":18,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-29T17:52:59.346637Z","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":"2026-07-10T06:15:00.866473Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2402.12289","last_updated":"2024-06-25T17:55:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-19T17:04:04Z","title":"DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models","version":5},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-12T19:22:35.305220Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2402.12289"},"observation_digest":"sha256:dbc7f7782f2b67bafb4b42b2f1111dc37cef0ee4791fbd27ababff77a1bdd7b1","observation_id":"09a61a38-c4c6-449b-bfb4-bf7e01ac4fca","resolution":{"observed_at":"2026-05-12T19:22:35.510642Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2408.13257","last_updated":"2025-02-05T08:44:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-23T17:59:51Z","title":"MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-16T07:59:32.638758Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2408.13257"},"observation_digest":"sha256:24cbc3bc0390de1a4c5645f3aaf9125f7f7aa869f930739c7df3b55b72af60ae","observation_id":"e58f663b-80c5-413e-a746-562d82612804","resolution":{"observed_at":"2026-05-16T07:59:32.692729Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2410.22313","last_updated":"2024-10-29T17:53:56Z","snapshot_observed_at":"2026-07-31T01:16:26.372370Z","submitted_at":"2024-10-29T17:53:56Z","title":"Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-15T15:24:23.756052Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2410.22313"},"observation_digest":"sha256:e6ee034af86cc3faccaebc4ff745bfb48b2176700aaef13f464ae2213d6e611f","observation_id":"7beae691-896c-4d69-bee3-970cc8d8a687","resolution":{"observed_at":"2026-05-15T15:24:23.869042Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2411.18275","last_updated":"2026-04-21T10:31:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-11-27T12:09:43Z","title":"Visual Adversarial Attack on Vision-Language Models for Autonomous Driving","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-23T16:35:24.063578Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2411.18275"},"observation_digest":"sha256:c653381267d752723a013148c433d6b352a771aa33100128802e50f77b4b66a6","observation_id":"b9a3cdfa-faab-44df-9ba4-e424eca91138","resolution":{"observed_at":"2026-05-23T16:35:42.192052Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2503.07608","last_updated":"2025-03-10T17:59:42Z","snapshot_observed_at":"2026-07-31T18:13:22.567513Z","submitted_at":"2025-03-10T17:59:42Z","title":"AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-16T20:06:27.136345Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2503.07608"},"observation_digest":"sha256:aa8375f41b6306845f1fd85c7b4f09752415bf7ada8b11e720876d5cf4f14e46","observation_id":"ae8e2572-5414-49b8-b5bd-d3d6f04ca85d","resolution":{"observed_at":"2026-05-16T20:06:27.230069Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2505.16278","last_updated":"2026-05-18T09:58:49Z","snapshot_observed_at":"2026-07-06T21:28:20.028748Z","submitted_at":"2025-05-22T06:23:04Z","title":"DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-22T14:30:47.787654Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2505.16278"},"observation_digest":"sha256:306365a46745deb79a970dca5f87a67c6218e61c16fe9d8a9f1c5fc937cd2826","observation_id":"876aa8d1-78ce-433f-9c25-7c8c9fffd000","resolution":{"observed_at":"2026-05-22T14:31:40.662059Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2506.05442","last_updated":"2026-05-16T07:36:33Z","snapshot_observed_at":"2026-07-06T21:37:32.525040Z","submitted_at":"2025-06-05T12:59:35Z","title":"Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-22T00:16:35.823270Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2506.05442"},"observation_digest":"sha256:c8b440774b8ca6720ecace7fe423c5e737a6efd3f95020019b3627819629b8dd","observation_id":"ba3bd234-77d9-4c20-b061-2f2412f81c17","resolution":{"observed_at":"2026-05-22T00:20:50.519821Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2508.05269","last_updated":"2026-05-12T08:51:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-07T11:11:56Z","title":"B4DL: A Benchmark for 4D LiDAR LLM in Spatio-Temporal Understanding","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-19T00:09:57.236162Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2508.05269"},"observation_digest":"sha256:a41bf2be116a5e0024eb803821898ddf7486c94445d16579b5816267d2a4eea7","observation_id":"8f98ee6c-7d80-407f-a3e8-2db48c1b13e1","resolution":{"observed_at":"2026-05-19T00:11:55.934515Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2512.14044","last_updated":"2026-04-30T14:06:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-12-16T03:19:28Z","title":"OmniDrive-R1: Reinforcement-driven Interleaved Multi-modal Chain-of-Thought for Trustworthy Vision-Language Autonomous Driving","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-16T22:34:00.895252Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2512.14044"},"observation_digest":"sha256:300f55509b9104eb73ab0d694c90ef35a2e97e95f96700a5c1c6b356b2c2e10c","observation_id":"130f7f11-fe50-4878-a24d-315f3df4f5b1","resolution":{"observed_at":"2026-05-16T22:38:37.855821Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2604.05767","last_updated":"2026-04-12T15:09:44Z","snapshot_observed_at":"2026-07-06T22:54:26.231593Z","submitted_at":"2026-04-07T12:10:21Z","title":"Beyond the Beep: Scalable Collision Anticipation and Real-Time Explainability with BADAS-2.0","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T18:33:16.047297Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2604.05767"},"observation_digest":"sha256:0623c49dd1cf5e4d870ec462b84ee7be648a3bdd94a13ef00fc677dd0ca26383","observation_id":"e8c61c05-ce62-431a-9d42-9fe6fdf14a58","resolution":{"observed_at":"2026-05-11T00:25:50.376664Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2604.17915","last_updated":"2026-04-20T07:50:00Z","snapshot_observed_at":"2026-07-06T23:04:55.190916Z","submitted_at":"2026-04-20T07:50:00Z","title":"OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-10T04:27:24.653711Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2604.17915"},"observation_digest":"sha256:477a92c9fc574173d474b337f6cf682dd971fd0d5cc48780ff934625c87731e1","observation_id":"a73e39cb-9031-4e49-8181-e2df90c6408b","resolution":{"observed_at":"2026-05-11T11:56:25.086289Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2604.20460","last_updated":"2026-04-22T11:39:02Z","snapshot_observed_at":"2026-07-06T23:06:55.880484Z","submitted_at":"2026-04-22T11:39:02Z","title":"CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-10T01:31:40.267429Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2604.20460"},"observation_digest":"sha256:0336d3d454d469f8ad8f14ee41a6f25b0e891b4e1059ba242b5a1d3c63f3bb33","observation_id":"a7cfe32a-1c0b-4f7d-ac71-03f6c0cff581","resolution":{"observed_at":"2026-05-11T13:31:05.488460Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2604.22851","last_updated":"2026-07-07T12:47:51Z","snapshot_observed_at":"2026-07-12T18:45:30.417168Z","submitted_at":"2026-04-22T07:49:02Z","title":"EgoDyn-Bench: Evaluating Ego-Motion Understanding in Vision-Centric Foundation Models for Autonomous Driving","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T00:09:18.068337Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2604.22851"},"observation_digest":"sha256:172a70d780c336f7e3e3d3a045766d005dd7148cd5d1e0012c9fca4fe5c51796","observation_id":"a191e450-f9fa-48a3-9ef6-506ea61c086d","resolution":{"observed_at":"2026-05-10T00:19:47.225470Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2605.00907","last_updated":"2026-04-29T04:29:48Z","snapshot_observed_at":"2026-07-06T23:14:15.780028Z","submitted_at":"2026-04-29T04:29:48Z","title":"TRIP-Evaluate: An Open Multimodal Benchmark for Evaluating Large Models in Transportation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-09T20:13:06.376037Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2605.00907"},"observation_digest":"sha256:77715bd2fed95fb882b3fc0bf5a74d464008298c2701d94d70407d734129e268","observation_id":"84c51a34-ee49-4b49-8d40-202c7726edc1","resolution":{"observed_at":"2026-05-09T20:17:04.496759Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2605.14696","last_updated":"2026-05-14T11:12:23Z","snapshot_observed_at":"2026-07-06T23:26:04.286377Z","submitted_at":"2026-05-14T11:12:23Z","title":"EponaV2: Driving World Model with Comprehensive Future Reasoning","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-15T05:14:28.714494Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2605.14696"},"observation_digest":"sha256:2a971edf69b1b3b185e52a44978a7641f57af77cb5711e18a292dee033b0b100","observation_id":"4bce54b4-283b-4444-9efa-97c5b8abed7b","resolution":{"observed_at":"2026-05-15T05:15:02.561817Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2605.23270","last_updated":"2026-05-22T06:17:35Z","snapshot_observed_at":"2026-07-06T23:33:29.550551Z","submitted_at":"2026-05-22T06:17:35Z","title":"ChainFlow-VLA: Causal Flow Planning with Vision-Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-25T04:37:56.487048Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2605.23270"},"observation_digest":"sha256:20b63ed2175d4057785b4d26007f7891d86d5c934593f9ff3dc005878cc49fff","observation_id":"1c1c84cf-2d65-45d7-b5e0-ff903a848dbe","resolution":{"observed_at":"2026-05-25T04:40:23.776537Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2605.27365","last_updated":"2026-05-27T02:30:49Z","snapshot_observed_at":"2026-07-06T23:37:08.167449Z","submitted_at":"2026-05-26T17:59:12Z","title":"LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-29T17:52:59.346637Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2605.27365"},"observation_digest":"sha256:c59664527abf62ab70b1ae7d4b1ba745aacf6863235afc39662015f627ff87a7","observation_id":"04a2be31-f9df-4bc2-8ed0-b4bd39c7f42e","resolution":{"observed_at":"2026-06-29T17:53:46.756827Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering","version":3},"cited_work":{"arxiv_id":"2312.14150","doi":"10.48550/arxiv.2312.14150","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.14150","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Drivelm: Driving with graph visual question answering.arXiv preprint arXiv:2312.14150","venue":null,"work_id":"e96d9f6a-db3a-442d-9a76-d703faaf10fa","year":2024},"citing_paper":{"arxiv_id":"2606.21165","last_updated":"2026-06-19T07:00:14Z","snapshot_observed_at":"2026-07-30T17:29:16.285279Z","submitted_at":"2026-06-19T07:00:14Z","title":"OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Driving","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-26T14:24:07.496389Z"},"links":{"cited_paper":"/paper/2312.14150","citing_paper":"/paper/2606.21165"},"observation_digest":"sha256:5907ad0a5486da391155d37652a8ec10729896f84f4771313b9cab0a0f5b69da","observation_id":"495e8542-65ba-441e-a483-bfad53d224c9","resolution":{"observed_at":"2026-07-04T06:29:38.033869Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-01T06:32:01.292127+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.14150/citation-record","integrity":"/paper/2312.14150/integrity","json":"/paper/2312.14150/citation-record.json","paper":"/paper/2312.14150"},"outbound":[],"paper":{"arxiv_id":"2312.14150","last_updated":"2025-01-16T10:57:44Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-21T18:59:12Z","title":"DriveLM: Driving with Graph Visual Question Answering"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"thesis":"As of 1 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2312.14150."}