{"as_of":"2026-08-07T12:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c8da7577b8323b52f79720c02dfc11c8def2311d24f2c8aec606f21ffd1bb613","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:51:08.269551Z","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":"2026-06-29T10:33:18.351723Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-08-07T05:51:08.269551Z","title":"and Zhang, T","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06971","last_updated":"2025-06-12T14:47:31Z","snapshot_observed_at":"2026-08-07T07:20:17.397323Z","submitted_at":"2025-06-08T02:43:46Z","title":"Chain-of-Code Collapse: Reasoning Failures in LLMs via Adversarial Prompting in Code Generation","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T05:51:08.269551Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2506.06971"},"observation_digest":"sha256:2a6f9c7c20ddc42f65c854879f320a516421598d2cef4d2aa402e7f1f4deca1a","observation_id":"20ac46b0-20b6-4df8-954f-b7a22e8fb6c9","resolution":{"observed_at":"2026-08-07T05:51:08.269551Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-08-07T00:40:26.249510Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13832","last_updated":"2025-06-18T13:10:14Z","snapshot_observed_at":"2026-08-07T04:40:03.152095Z","submitted_at":"2025-06-16T03:20:31Z","title":"FrontendBench: A Benchmark for Evaluating LLMs on Front-End Development via Automatic Evaluation","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T00:40:26.249510Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2506.13832"},"observation_digest":"sha256:7fbaf68589d52726ceb3fc82d82585985edcbe1273f207b2c538ab4197127ae5","observation_id":"e31c68b0-1d1c-4ae7-9254-938acc54e847","resolution":{"observed_at":"2026-08-07T00:40:26.249510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-08-06T20:09:18.412504Z","title":"arXiv preprint arXiv:2410.02184 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.03620","last_updated":"2025-07-04T14:46:56Z","snapshot_observed_at":"2026-08-06T20:03:12.961272Z","submitted_at":"2025-07-04T14:46:56Z","title":"Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:09:18.412504Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2507.03620"},"observation_digest":"sha256:80d3ca80d0825e6834b7dceebe6a6afc3a1fae560f0bc34ee27eec0e6113e6f4","observation_id":"02084f4a-0f73-458f-a9c5-d6565fd1facc","resolution":{"observed_at":"2026-08-06T20:09:18.412504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-08-06T19:09:33.177676Z","title":"CodeJudge: Evaluating code generation with large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.06463","last_updated":"2025-08-28T14:22:23Z","snapshot_observed_at":"2026-08-06T19:01:30.560315Z","submitted_at":"2025-07-09T00:46:30Z","title":"Evaluating Efficiency and Novelty of LLM-Generated Code for Graph Analysis","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:09:33.177676Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2507.06463"},"observation_digest":"sha256:c7df445f88ea2db446b15b368a4650bb2da0b6ee556cbaedbf29a4adc0a539a1","observation_id":"993294e3-f724-4824-9305-34f4c5531b9c","resolution":{"observed_at":"2026-08-06T19:09:33.177676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-08-06T17:43:53.893783Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.10088","last_updated":"2025-07-14T09:15:22Z","snapshot_observed_at":"2026-08-06T17:37:25.079459Z","submitted_at":"2025-07-14T09:15:22Z","title":"Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T17:43:53.893783Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2507.10088"},"observation_digest":"sha256:b810ab9dedbadf904a2a3b4f4008f90bc00a7145aef3f0df2529329c1ec376aa","observation_id":"a5684bfc-50b1-436c-bc04-6f42c4ab0d8b","resolution":{"observed_at":"2026-08-06T17:43:53.893783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-08-05T14:57:12.918674Z","title":"Codejudge: Evaluating code generation with large language models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.20766","last_updated":"2025-08-28T13:22:33Z","snapshot_observed_at":"2026-08-07T06:46:21.394571Z","submitted_at":"2025-08-28T13:22:33Z","title":"Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-05T14:57:12.918674Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2508.20766"},"observation_digest":"sha256:d4be71835df6d536f43f23976689c1a466dcf34178dae46524cfb933877a083a","observation_id":"99dd246e-57ef-45d8-b199-ff87eda4e38a","resolution":{"observed_at":"2026-08-05T14:57:12.918674Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-08-04T10:27:35.142542Z","title":"Ngoc Tran, Hieu Tran, Son Nguyen, Hoan Nguyen, and Tien N","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.09898","last_updated":"2026-06-22T05:04:21Z","snapshot_observed_at":"2026-08-04T10:27:34.315916Z","submitted_at":"2025-10-10T22:22:36Z","title":"Learning Bug Context for PyTorch-to-JAX Translation with LLMs","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T10:27:35.142542Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2510.09898"},"observation_digest":"sha256:bd127a71ff36bf819ca29004802f2b970f0ef873694a4e46e3a4a91de28104d8","observation_id":"8e32c244-ca40-4063-aa2f-1210f4329423","resolution":{"observed_at":"2026-08-04T10:27:35.142542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":"2410.02184","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-06-29T10:33:18.351723Z","title":"Codejudge: Evaluating code generation with large language models.arXiv preprint arXiv:2410.02184,","venue":null,"work_id":"82eafecf-eb6d-4014-89ad-6904fcbcfb10","year":2024},"citing_paper":{"arxiv_id":"2604.16790","last_updated":"2026-04-18T02:35:05Z","snapshot_observed_at":"2026-07-06T23:04:01.558812Z","submitted_at":"2026-04-18T02:35:05Z","title":"Bias in the Loop: Auditing LLM-as-a-Judge for Software Engineering","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T07:29:03.994957Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2604.16790"},"observation_digest":"sha256:81641b963ebb26072da02257942d3ec6d664b208d42116aeedc396bc3703146c","observation_id":"8a579457-f3c7-4005-8dd2-e542a2a1b0ba","resolution":{"observed_at":"2026-05-10T07:32:00.299021Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":"2410.02184","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-06-29T10:33:18.351723Z","title":"Codejudge: Evaluating code generation with large language models.arXiv preprint arXiv:2410.02184,","venue":null,"work_id":"82eafecf-eb6d-4014-89ad-6904fcbcfb10","year":2024},"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":120,"source":"pdf_text","source_observed_at":"2026-05-08T17:37:51.790000Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2605.05267"},"observation_digest":"sha256:17c609e7d9ffa8abd403678d417fa54fb7de9ece5565ec76c6587da76f6b806b","observation_id":"bf8e60b2-5bb8-45e7-aad0-d68353fa3b8c","resolution":{"observed_at":"2026-05-11T17:21:10.923396Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":"2410.02184","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-06-29T10:33:18.351723Z","title":"Codejudge: Evaluating code generation with large language models.arXiv preprint arXiv:2410.02184,","venue":null,"work_id":"82eafecf-eb6d-4014-89ad-6904fcbcfb10","year":2024},"citing_paper":{"arxiv_id":"2606.00118","last_updated":"2026-05-27T19:42:01Z","snapshot_observed_at":"2026-08-05T19:06:05.803113Z","submitted_at":"2026-05-27T19:42:01Z","title":"An Empirical Study on Logging Evolution On Stack Overflow: Trends, Topics, and Challenges","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-29T10:32:47.756343Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2606.00118"},"observation_digest":"sha256:01c4e8a263ffb3bdfff4926cbcff6659f26472bc87abb08ba1316e7645646112","observation_id":"ed1ecbac-7bed-4c14-bac5-d51876a639ff","resolution":{"observed_at":"2026-06-29T10:33:18.354032Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02184","snapshot_observed_at":"2026-07-11T21:45:42.517559Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04092","last_updated":"2026-07-05T03:07:10Z","snapshot_observed_at":"2026-08-03T22:15:29.379932Z","submitted_at":"2026-07-05T03:07:10Z","title":"SEDCoT: Enhancing LLM-Based COBOL Code Translation via Symbolic Execution and Delta Debugging","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-07-11T21:45:42.517559Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2607.04092"},"observation_digest":"sha256:c2431497075dd431079a16909a5ab042d50762226870fbbe2e771692ef5d429f","observation_id":"ecaec7ad-eab9-4870-bfb7-b8ac3a5232ec","resolution":{"observed_at":"2026-07-11T21:45:42.517559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.02184/citation-record","integrity":"/paper/2410.02184/integrity","json":"/paper/2410.02184/citation-record.json","paper":"/paper/2410.02184"},"outbound":[],"paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T19:26:43.399756Z","submitted_at":"2024-10-03T03:58:03Z","title":"CodeJudge: Evaluating Code Generation with Large Language Models"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2410.02184."}