{"as_of":"2026-08-08T23:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1e4ae92fc4690522ba0d18297ca5886d772b761826cca50a28266f87b598f383","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T12:37:25.739601Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T18:21:08.457601Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.12596","last_updated":"2023-12-15T01:17:35Z","snapshot_observed_at":"2026-08-07T09:35:47.528676Z","submitted_at":"2023-07-24T08:14:22Z","title":"Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.12596","snapshot_observed_at":"2026-08-08T12:37:25.739601Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.07487","last_updated":"2025-02-11T11:46:38Z","snapshot_observed_at":"2026-08-08T12:32:06.365109Z","submitted_at":"2025-02-11T11:46:38Z","title":"Multi-Agent Collaboration for Multilingual Code Instruction Tuning","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-08T12:37:25.739601Z"},"links":{"cited_paper":"/paper/2307.12596","citing_paper":"/paper/2502.07487"},"observation_digest":"sha256:0f2760fcc8671bea47aab5ed99fbdd2eead6089372bb6256037d62fc56b9eb70","observation_id":"156f0c14-1675-4b2c-8ac2-1261bce14723","resolution":{"observed_at":"2026-08-08T12:37:25.739601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.12596","last_updated":"2023-12-15T01:17:35Z","snapshot_observed_at":"2026-08-07T09:35:47.528676Z","submitted_at":"2023-07-24T08:14:22Z","title":"Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.12596","snapshot_observed_at":"2026-08-06T17:51:13.673581Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09866","last_updated":"2025-07-14T02:36:27Z","snapshot_observed_at":"2026-08-06T17:43:03.446373Z","submitted_at":"2025-07-14T02:36:27Z","title":"Turning the Tide: Repository-based Code Reflection","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T17:51:13.673581Z"},"links":{"cited_paper":"/paper/2307.12596","citing_paper":"/paper/2507.09866"},"observation_digest":"sha256:d74757fd90ba50234e14b3fa94decd53547f4e1dc4b1872f67c1b8f446f87562","observation_id":"d379973e-b1ec-4f78-9dc3-e41704123d9f","resolution":{"observed_at":"2026-08-06T17:51:13.673581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.12596","last_updated":"2023-12-15T01:17:35Z","snapshot_observed_at":"2026-08-07T09:35:47.528676Z","submitted_at":"2023-07-24T08:14:22Z","title":"Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.12596","snapshot_observed_at":"2026-08-06T16:34:09.247523Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.13123","last_updated":"2025-07-17T13:38:16Z","snapshot_observed_at":"2026-08-08T09:20:46.381860Z","submitted_at":"2025-07-17T13:38:16Z","title":"Detecting LLM-generated Code with Subtle Modification by Adversarial Training","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:34:09.247523Z"},"links":{"cited_paper":"/paper/2307.12596","citing_paper":"/paper/2507.13123"},"observation_digest":"sha256:cdd2c9e0f8ec572bf9f4001bf9309241de49ffe4be2033f65f600dbda9eb0330","observation_id":"0dbd655c-72e5-4386-9b80-acc64f53f4ff","resolution":{"observed_at":"2026-08-06T16:34:09.247523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.12596","last_updated":"2023-12-15T01:17:35Z","snapshot_observed_at":"2026-08-07T09:35:47.528676Z","submitted_at":"2023-07-24T08:14:22Z","title":"Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues","version":2},"cited_work":{"arxiv_id":"2307.12596","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.12596","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Refining ChatGPT- Generated Code: Characterizing and Mitigating Code Quality Issues","venue":null,"work_id":"f3bad0c6-0613-49e9-9810-6de70069da53","year":2023},"citing_paper":{"arxiv_id":"2605.04835","last_updated":"2026-05-06T12:31:49Z","snapshot_observed_at":"2026-07-31T17:31:30.979223Z","submitted_at":"2026-05-06T12:31:49Z","title":"Patterns of Developer Adoption of LLM-Generated Code Refactoring Suggestions","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T16:14:02.698829Z"},"links":{"cited_paper":"/paper/2307.12596","citing_paper":"/paper/2605.04835"},"observation_digest":"sha256:dc3bcd22b032494d1f35c88541c60c085b0276be5088d4a6874ecd955b854c7e","observation_id":"0b311550-7188-408b-9b83-1eb9d2f0e6bd","resolution":{"observed_at":"2026-05-11T18:21:08.462254Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.12596","last_updated":"2023-12-15T01:17:35Z","snapshot_observed_at":"2026-08-07T09:35:47.528676Z","submitted_at":"2023-07-24T08:14:22Z","title":"Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues","version":2},"cited_work":{"arxiv_id":"2307.12596","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.12596","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Refining ChatGPT- Generated Code: Characterizing and Mitigating Code Quality Issues","venue":null,"work_id":"f3bad0c6-0613-49e9-9810-6de70069da53","year":2023},"citing_paper":{"arxiv_id":"2605.05267","last_updated":"2026-05-06T09:38:31Z","snapshot_observed_at":"2026-08-04T17:41:12.164736Z","submitted_at":"2026-05-06T09:38:31Z","title":"Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-08T17:37:51.790000Z"},"links":{"cited_paper":"/paper/2307.12596","citing_paper":"/paper/2605.05267"},"observation_digest":"sha256:e3598d9e5b110a5e5616f22b689815a2b86f4622c80b3d00825ecdce20e7f2fc","observation_id":"22c52c8a-aad1-43c8-a0dc-1e9d84d3b3fd","resolution":{"observed_at":"2026-05-11T17:21:11.020168Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2307.12596/citation-record","integrity":"/paper/2307.12596/integrity","json":"/paper/2307.12596/citation-record.json","paper":"/paper/2307.12596"},"outbound":[],"paper":{"arxiv_id":"2307.12596","last_updated":"2023-12-15T01:17:35Z","latest_version":2,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-07T09:35:47.528676Z","submitted_at":"2023-07-24T08:14:22Z","title":"Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"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."}