Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Survey on Multimodal Large Language Models for Autonomous Driving
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2311.12320.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-30T16:40:22.441025Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T20:56:14.194881Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation d211e8af-0f49-49fd-8ddb-ae3ad290da68 · inbound
LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios cites this paper.
LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios A Survey on Multimodal Large Language Models for Autonomous Driving
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T13:21:35.749047Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 79d6e4a0-9ea9-4e58-8161-1dfb896e4caf · inbound
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving A Survey on Multimodal Large Language Models for Autonomous Driving
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T05:15:22.922015Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2a7938e7-7066-4654-946c-825b7f270d77 · inbound
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving A Survey on Multimodal Large Language Models for Autonomous Driving
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T16:44:56.048382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b9e1b5b8-43b9-4478-91cd-3905db0fa7cd · inbound
Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support cites this paper.
Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support A Survey on Multimodal Large Language Models for Autonomous Driving
Reference 37
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T20:56:14.196485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.