Paper Citation Record · LEDGER

Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2404.10595.

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

pith.paper-citation-record.v1
2404.10595 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:37:43.421592Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:09:44.920516Z

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 06a2b402-bc3c-4615-a91f-b7e0db843511 · inbound

A Survey on LLM-as-a-Judge cites this paper.

A Survey on LLM-as-a-Judge Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:35:44.144326Z

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 cd1b1fc6-3236-4e6d-90bb-1d9f758fc1be · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:08:36.118545Z

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 5f5fbd76-3146-46e4-b874-bccda0abfc58 · inbound

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving cites this paper.

ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:36:24.385455Z

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 f75bcb01-631b-40ea-904d-0508db5d7e0d · inbound

MoSE: Skill-by-Skill Mixture-of-Experts Learning for Embodied Autonomous Machines cites this paper.

MoSE: Skill-by-Skill Mixture-of-Experts Learning for Embodied Autonomous Machines Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T18:37:43.421592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44dea1fb-3413-481d-8c86-6501d926bea7 · inbound

SafeDriveRAG: Towards Safe Autonomous Driving with Knowledge Graph-based Retrieval-Augmented Generation cites this paper.

SafeDriveRAG: Towards Safe Autonomous Driving with Knowledge Graph-based Retrieval-Augmented Generation Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T12:43:09.823740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90c76992-5bf4-4887-b4b3-6d43bd02fd41 · inbound

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case cites this paper.

RoboTron-Sim: Improving Real-World Driving via Simulated Hard-Case Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T23:53:45.537163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb0c6530-a47d-4758-8105-b6a212e6a0fe · inbound

Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving cites this paper.

Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:09:44.921998Z

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.