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Paper Citation Record · LEDGER

Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2307.12596.

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

pith.paper-citation-record.v1
2307.12596 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:37:25.739601Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T18:21:08.457601Z

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 156f0c14-1675-4b2c-8ac2-1261bce14723 · inbound

Multi-Agent Collaboration for Multilingual Code Instruction Tuning cites this paper.

Multi-Agent Collaboration for Multilingual Code Instruction Tuning Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-08T12:37:25.739601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T12:37:25.739601Z digest=sha256:0f2760fcc8671bea47aab5ed99fbdd2eead6089372bb6256037d62fc56b9eb70

Observation d379973e-b1ec-4f78-9dc3-e41704123d9f · inbound

Turning the Tide: Repository-based Code Reflection cites this paper.

Turning the Tide: Repository-based Code Reflection Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T17:51:13.673581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:51:13.673581Z digest=sha256:d74757fd90ba50234e14b3fa94decd53547f4e1dc4b1872f67c1b8f446f87562

Observation 0dbd655c-72e5-4386-9b80-acc64f53f4ff · inbound

Detecting LLM-generated Code with Subtle Modification by Adversarial Training cites this paper.

Detecting LLM-generated Code with Subtle Modification by Adversarial Training Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T16:34:09.247523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:34:09.247523Z digest=sha256:cdd2c9e0f8ec572bf9f4001bf9309241de49ffe4be2033f65f600dbda9eb0330

Observation 0b311550-7188-408b-9b83-1eb9d2f0e6bd · inbound

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions cites this paper.

Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:21:08.462254Z

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=2026-05-08T16:14:02.698829Z digest=sha256:dc3bcd22b032494d1f35c88541c60c085b0276be5088d4a6874ecd955b854c7e

Observation 22c52c8a-aad1-43c8-a0dc-1e9d84d3b3fd · 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 Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues

Reference 77

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:21:11.020168Z

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=2026-05-08T17:37:51.790000Z digest=sha256:e3598d9e5b110a5e5616f22b689815a2b86f4622c80b3d00825ecdce20e7f2fc