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Paper Citation Record · LEDGER

CodeJudge: Evaluating Code Generation with Large Language Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2410.02184.

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

pith.paper-citation-record.v1
2410.02184 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:38:21.633711Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T10:33:18.351723Z

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 eccc0eee-4acb-46da-bf1f-d88002ce1be3 · inbound

Bridging LLM-Generated Code and Requirements: Reverse Generation technique and SBC Metric for Developer Insights cites this paper.

Bridging LLM-Generated Code and Requirements: Reverse Generation technique and SBC Metric for Developer Insights CodeJudge: Evaluating Code Generation with Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-08T13:38:21.633711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:38:21.633711Z digest=sha256:b563ed5f772f99f8784f788d8228f5fcc5a16b2b49061dc68db2a3d73b2b1981

Observation 20ac46b0-20b6-4df8-954f-b7a22e8fb6c9 · inbound

Chain-of-Code Collapse: Reasoning Failures in LLMs via Adversarial Prompting in Code Generation cites this paper.

Chain-of-Code Collapse: Reasoning Failures in LLMs via Adversarial Prompting in Code Generation CodeJudge: Evaluating Code Generation with Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T05:51:08.269551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:51:08.269551Z digest=sha256:ed8bfc94eeda33b3d1ca388bd62f8835d8bac86e40aeea9cf702c2c1efcbe956

Observation e31c68b0-1d1c-4ae7-9254-938acc54e847 · inbound

FrontendBench: A Benchmark for Evaluating LLMs on Front-End Development via Automatic Evaluation cites this paper.

FrontendBench: A Benchmark for Evaluating LLMs on Front-End Development via Automatic Evaluation CodeJudge: Evaluating Code Generation with Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:26.249510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:26.249510Z digest=sha256:c74847992853bafcf0b94e7fbf51626d833971808c0c1d3fd708e927fbe19729

Observation 02084f4a-0f73-458f-a9c5-d6565fd1facc · inbound

Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy cites this paper.

Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy CodeJudge: Evaluating Code Generation with Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T20:09:18.412504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:09:18.412504Z digest=sha256:69d3496233a0e2c7ea4559fbe7314e039377490f1f84840070003e27539b980f

Observation 993294e3-f724-4824-9305-34f4c5531b9c · inbound

Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis cites this paper.

Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis CodeJudge: Evaluating Code Generation with Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:33.177676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:09:33.177676Z digest=sha256:aa3722ae801f3b7fbae251b2db87b4ab5f6ed49459fe6d23f123f4c83b151214

Observation a5684bfc-50b1-436c-bc04-6f42c4ab0d8b · inbound

Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering cites this paper.

Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering CodeJudge: Evaluating Code Generation with Large Language Models

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T17:43:53.893783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:43:53.893783Z digest=sha256:0e5d5a1da9f41175fd5bced0a148a477aa1cdd4e7456b2c92df3d233486b2b0a

Observation 99dd246e-57ef-45d8-b199-ff87eda4e38a · inbound

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection cites this paper.

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection CodeJudge: Evaluating Code Generation with Large Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-05T14:57:12.918674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:57:12.918674Z digest=sha256:6a8916eaa9030077d8d83bbc15766a9de5c1b0bc505a6337ea3641734d0d4862

Observation 8e32c244-ca40-4063-aa2f-1210f4329423 · inbound

Learning Bug Context for PyTorch-to-JAX Translation with LLMs cites this paper.

Learning Bug Context for PyTorch-to-JAX Translation with LLMs CodeJudge: Evaluating Code Generation with Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-04T10:27:35.142542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T10:27:35.142542Z digest=sha256:b57213610fdc931393edc58713b93fb7517c1c2aeb591088239c347142cf066a

Observation 8a579457-f3c7-4005-8dd2-e542a2a1b0ba · 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: Evaluating Code Generation with Large Language Models

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:32:00.299021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T07:29:03.994957Z digest=sha256:1f6bf9490ae433a4e9087346a7013fcf795dc183173a412ef16df046931bc7fa

Observation bf8e60b2-5bb8-45e7-aad0-d68353fa3b8c · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code CodeJudge: Evaluating Code Generation with Large Language Models

Reference 120

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:21:10.923396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-08T17:37:51.790000Z digest=sha256:b2f61ed51ec8a579a79981f764d41a90fa20fed19a5a921d167986e4552f6849

Observation ed1ecbac-7bed-4c14-bac5-d51876a639ff · inbound

An Empirical Study on Logging Evolution On Stack Overflow: Trends, Topics, and Challenges cites this paper.

An Empirical Study on Logging Evolution On Stack Overflow: Trends, Topics, and Challenges CodeJudge: Evaluating Code Generation with Large Language Models

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-06-29T10:33:18.354032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T10:32:47.756343Z digest=sha256:d9e981f3dd813dfb31e04c7f8e5e4f87789b2adb39f52d97d16c5623419a7fab

Observation ecaec7ad-eab9-4870-bfb7-b8ac3a5232ec · inbound

SEDCoT: Enhancing LLM-Based COBOL Code Translation via Symbolic Execution and Delta Debugging cites this paper.

SEDCoT: Enhancing LLM-Based COBOL Code Translation via Symbolic Execution and Delta Debugging CodeJudge: Evaluating Code Generation with Large Language Models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-07-11T21:45:42.517559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:45:42.517559Z digest=sha256:b2bdc600c7ff485120c283b1585084d8d7a9a331a5f11c50253ec07bb48a5cf5