Paper Citation Record · LEDGER

CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.10718.

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

pith.paper-citation-record.v1
2408.10718 v2

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 2026-08-16T06:30:59.297886+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:50:50.690353Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T17:35:44.171248Z

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 b5c19431-5940-4394-a6e7-465c85ba4efa · inbound

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

A Survey on LLM-as-a-Judge CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Reference 219

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:35:44.174084Z

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 6d27ed5e-6df0-4916-8a91-08e3c4982c17 · inbound

Evaluate-and-Purify: Fortifying Code Language Models Against Adversarial Attacks Using LLM-as-a-Judge cites this paper.

Evaluate-and-Purify: Fortifying Code Language Models Against Adversarial Attacks Using LLM-as-a-Judge CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T05:50:50.690353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c59a42ba-7e1d-4028-9e5f-267ad9b6eeb7 · inbound

Is Your Automated Software Engineer Trustworthy? cites this paper.

Is Your Automated Software Engineer Trustworthy? CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T19:06:53.978307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1db605c3-6c3c-4b88-be35-b78c37460583 · inbound

ReCatcher: Towards LLMs Regression Testing for Code Generation cites this paper.

ReCatcher: Towards LLMs Regression Testing for Code Generation CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T17:57:05.981261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 195b9ce0-c22c-4dfb-a4ab-6043b7c4c515 · inbound

Enhancing Large Language Models with Retrieval Augmented Generation for Software Testing and Inspection Automation cites this paper.

Enhancing Large Language Models with Retrieval Augmented Generation for Software Testing and Inspection Automation CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-10T10:44:38.021334Z

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 8d28c040-a207-4ebe-b0be-c058de436af6 · inbound

Bias in the Loop: Auditing LLM-as-a-Judge for Software Engineering cites this paper.

Bias in the Loop: Auditing LLM-as-a-Judge for Software Engineering CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-10T07:32:00.279793Z

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 8b33dec6-9523-40c2-b587-d803d99e5a26 · inbound

PYTHALAB-MERA: Validation-Grounded Memory, Retrieval, and Acceptance Control for Frozen-LLM Coding Agents cites this paper.

PYTHALAB-MERA: Validation-Grounded Memory, Retrieval, and Acceptance Control for Frozen-LLM Coding Agents CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:21:26.012242Z

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.