Pith. sign in

Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 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 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:47:51.695489Z

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T17:33:13.394338Z digest=sha256:0e2ea30ffa7a93c622722a84e355a250abc18099b60acb7a23ac6a8b0220b5f8

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T23:08:34.312466Z digest=sha256:17fc9be04765bb9aab08e1b5eea98d9c6daf21cf9199d44d95e3fcb057793d61

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T07:36:24.319361Z digest=sha256:cdbe16b617c196c3424cf1ac4c8de5c97168b18ac7b2da2e7a43cbe279554bb1

Observation c552567c-7a2a-4943-8a1d-4de282fce5c9 · inbound

ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving cites this paper.

ECCV 2024 W-CODA: 1st Workshop on Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:51.695489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:51.695489Z digest=sha256:60389739687af709a547fc66228efa456898595943d795f4c3d74d20c52e927b

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.

source=arxiv_source observed=2026-08-06T18:37:43.421592Z digest=sha256:835932e6abffc64f016325fb9a409f755872ae0a35feab814426f04a1d0866ec

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.

source=pdf_text observed=2026-08-06T12:43:09.823740Z digest=sha256:f3d80d86441bf6990e921d5bf886ec624137a5218d95812913ee6375e75486d4

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.

source=pdf_text observed=2026-08-05T23:53:45.537163Z digest=sha256:72f080d9a36fff2f7eb69895844e5431cddaaf961658824916a0ec79273c502c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T09:06:54.669489Z digest=sha256:cb2fe9698d80b52928e9e7c479bcdbc28cdf110bb7f6de879a6c56c7e171e3f9