{"as_of":"2026-08-19T03:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:41ae77c54ecd46cacfde3d5e74e8269bb8eb5839f16b7c75df8006326f6f0082","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":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":13,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T05:50:50.627403Z","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-08T13:38:21.633711Z","title":"Codejudge: Evaluating code generation with large lan- guage models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.07835","last_updated":"2025-02-11T01:12:11Z","snapshot_observed_at":"2026-08-18T19:43:10.491394Z","submitted_at":"2025-02-11T01:12:11Z","title":"Bridging LLM-Generated Code and Requirements: Reverse Generation technique and SBC Metric for Developer Insights","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T13:38:21.633711Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2502.07835"},"observation_digest":"sha256:034b020961921d6dc6f5a1730f5c5b1b9bdd3e832ab49416f5457e672d3388db","observation_id":"eccc0eee-4acb-46da-bf1f-d88002ce1be3","resolution":{"observed_at":"2026-08-08T13:38:21.633711Z","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-16T05:50:50.627403Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.19730","last_updated":"2025-04-28T12:28:55Z","snapshot_observed_at":"2026-08-16T05:42:40.103725Z","submitted_at":"2025-04-28T12:28:55Z","title":"Evaluate-and-Purify: Fortifying Code Language Models Against Adversarial Attacks Using LLM-as-a-Judge","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T05:50:50.627403Z"},"links":{"cited_paper":"/paper/2410.02184","citing_paper":"/paper/2504.19730"},"observation_digest":"sha256:6fdb5cdeeaa97082421b0210662e4a4f1d5fa425cc4ab8caf4d19d8bbb7389c6","observation_id":"fffbd3d3-0e42-4286-b61d-df14f6face8f","resolution":{"observed_at":"2026-08-16T05:50:50.627403Z","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-18T10:44:41.332250Z","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":"sha256:4ceab45e11d0f4dabc7643078b9d44caacfbdca271cfc3b7acbc6e900409da9c","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-16T02:15:14.732809Z","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":"sha256:91d70534274151e135435fda678c7a98edcd2d39e619c92aea0ba50766af2327","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-18T13:15:48.994766Z","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":"sha256:97892416bbc75583fce84f88ff6c46ae974ae7ed3c7a4375cb224deec30308d8","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-15T13:01:37.258518Z","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":"sha256:71948f57e1aa92a0270efc69b69b5ccf9f0301bfdf0f3f26624ee2ef44769213","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-16T07:00:31.438247Z","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:a0f5a545cf86f7059a6311951df39f97727c3699cb68b6201ca0cdc095b3bdd6","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-16T04:06:07.476971Z","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:ef760e390a18fd3c377ecef9f84a4f94b3d7ed96245b12469324c755c1a7d7f7","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-13T13:06:54.305456Z","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":"sha256:3aa0c83494880b797522c0febc1a425299e480287c3179107cb72975d514dfbd","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-15T10:37:57.254986Z","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:f37e7c9f73d1c71578f04f5d378735c59806152ae4255a725eb14d4ca889f1ef","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 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-08-17T01:49:43.647946Z","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":"sha256:5eccd3d2ab9dae2dfbce49d2803b6fb54ba23e56ceac59efff64d5b5e1635ce8","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 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-08-17T01:49:43.647946Z","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":"2026-08-14T03:09:36.364059Z","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":"sha256:1e5adf4152b22a39b30dc36560a63cb681e21a02962feee3f2b1c146e5fa2c1d","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 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02184","last_updated":"2024-10-03T03:58:03Z","snapshot_observed_at":"2026-08-17T01:49:43.647946Z","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":"2026-08-14T14:49:05.499440Z","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":"sha256:1790833d2db26aad7c1ee534d55992162d5e5d6969c0b87080ae400d620d00d5","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":"2026-08-17T01:49:43.647946Z","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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2410.02184."}