Paper Citation Record · LEDGER

CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.08683.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2503.08683 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:32:33.312942Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T06:29:38.021032Z

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 dc341487-bc0e-4aac-b890-0de8b8317808 · inbound

Automated Vehicles Should be Connected with Natural Language cites this paper.

Automated Vehicles Should be Connected with Natural Language CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T21:48:54.060647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c52f118a-c617-49d2-a96f-c4f6c9db638f · inbound

MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems cites this paper.

MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:51:27.494358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d6a62b20-7ca5-4789-bcb0-5db115b97d95 · inbound

EponaV2: Driving World Model with Comprehensive Future Reasoning cites this paper.

EponaV2: Driving World Model with Comprehensive Future Reasoning CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:15:02.696453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9ccebe21-e47a-4fb9-83e5-ceed6a445db8 · inbound

OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Driving cites this paper.

OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Driving CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-04T06:29:38.022862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8ab46e95-b50c-4aaa-b906-9391c555ca3e · inbound

Vision-Language Assistant for Emotional Reactions to Risky Driving cites this paper.

Vision-Language Assistant for Emotional Reactions to Risky Driving CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T21:10:54.806772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94a947ed-fbef-499f-90e6-aa3861f7806f · inbound

CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models cites this paper.

CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models CoLMDriver: LLM-based Negotiation Benefits Cooperative Autonomous Driving

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T00:32:33.312942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.