{"as_of":"2026-08-11T06:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bfdcf158db634551758312c8554872be113e03144beac1c3ae485daa98d5324e","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T11:26:57.829198Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-15T12:06:50.635891Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":"2501.16692","doi":"10.48550/arxiv.2501.16692","metadata_source":"arxiv_reference","pith_arxiv_id":"2501.16692","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"CoRR abs/2501.16692(2025).https : / / doi","venue":"ArXiv.org","work_id":"ceeb9176-bcf0-4bdf-b226-6352456bda58","year":2025},"citing_paper":{"arxiv_id":"2604.19750","last_updated":"2026-03-14T05:40:30Z","snapshot_observed_at":"2026-07-06T23:06:21.774788Z","submitted_at":"2026-03-14T05:40:30Z","title":"Coding with Eyes: Visual Feedback Unlocks Reliable GUI Code Generating and Debugging","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-15T12:06:50.635891Z"},"links":{"cited_paper":"/paper/2501.16692","citing_paper":"/paper/2604.19750"},"observation_digest":"sha256:e3b01ec9dc6c4d60759c256bf32f6bab0bba0d92af8247c8496ef1e6e60454e3","observation_id":"f0ed5981-3474-458c-a84a-1fb00fcb4255","resolution":{"observed_at":"2026-05-15T12:09:59.525520Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"cited_work":{"arxiv_id":"2501.16692","doi":"10.48550/arxiv.2501.16692","metadata_source":"arxiv_reference","pith_arxiv_id":"2501.16692","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"CoRR abs/2501.16692(2025).https : / / doi","venue":"ArXiv.org","work_id":"ceeb9176-bcf0-4bdf-b226-6352456bda58","year":2025},"citing_paper":{"arxiv_id":"2604.23940","last_updated":"2026-05-01T21:28:31Z","snapshot_observed_at":"2026-08-02T04:55:02.592639Z","submitted_at":"2026-04-27T01:28:11Z","title":"Constraint-Guided Multi-Agent Decompilation for Executable Binary Recovery","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T03:38:20.915757Z"},"links":{"cited_paper":"/paper/2501.16692","citing_paper":"/paper/2604.23940"},"observation_digest":"sha256:a48c40738525065a0bea9e9d3400b241a5e3f49590ad4bf90ca258a836d99e22","observation_id":"b4581dc6-caa5-4293-b158-81654cf7a301","resolution":{"observed_at":"2026-05-11T22:01:11.720646Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.16692/citation-record","integrity":"/paper/2501.16692/integrity","json":"/paper/2501.16692/citation-record.json","paper":"/paper/2501.16692"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.13630","last_updated":"2024-05-03T13:07:18Z","snapshot_observed_at":"2026-08-10T11:51:00.668881Z","submitted_at":"2024-04-21T12:06:05Z","title":"Utilizing Deep Learning to Optimize Software Development Processes","version":2},"cited_work":{"arxiv_id":"2404.13630","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.13630","snapshot_observed_at":"2026-08-10T11:26:58.310700Z","title":"Utilizing Deep Learning to Optimize Software Development Processes","venue":"cs.SE","work_id":"3186009a-bcef-4c4b-856e-de56cac66d95","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.693835Z"},"links":{"cited_paper":"/paper/2404.13630","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:54473256b139eca736b7cfdbb8039a1af59f3d124bc5b9bf32543c3a9292799d","observation_id":"b774e323-9866-4f7e-8620-f46c930a3e4a","resolution":{"observed_at":"2026-08-10T11:26:58.314153Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.07867","last_updated":"2024-04-26T16:41:55Z","snapshot_observed_at":"2026-08-09T00:08:03.125473Z","submitted_at":"2023-02-15T18:59:21Z","title":"Learning Performance-Improving Code Edits","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.07867","snapshot_observed_at":"2026-08-10T11:26:57.699026Z","title":"Learning performance-improving code edits,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.699026Z"},"links":{"cited_paper":"/paper/2302.07867","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:b499cebcf4e61c0826ea5717fc5d0971cdbae8e5519dfc9b93b158bbb62c6f47","observation_id":"614fb13d-81df-48b7-bbbc-48c6fa1a98ea","resolution":{"observed_at":"2026-08-10T11:26:57.699026Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.455228Z","title":"Search-based llms for code optimization,","venue":null,"work_id":"480e6f75-db89-4b5d-ae60-342dc2ef4912","year":2025},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.703030Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:c00b18757a713b66383a4bd5f666377d2a5ae0f0507773feb8a227a096b09764","observation_id":"82a4fcae-1a0c-4b3c-beed-3c4efb96c458","resolution":{"observed_at":"2026-08-10T11:26:58.459195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.02213","last_updated":"2023-12-03T07:03:04Z","snapshot_observed_at":"2026-08-10T22:36:35.176217Z","submitted_at":"2023-12-03T07:03:04Z","title":"JarviX: A LLM No code Platform for Tabular Data Analysis and Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.02213","snapshot_observed_at":"2026-08-10T11:26:57.706661Z","title":"Jarvix: A llm no code platform for tab- ular data analysis and optimization,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.706661Z"},"links":{"cited_paper":"/paper/2312.02213","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:e6cf8a13172ea6b1ddb8f827d20c76e3bf0ec53e9eb4ed09fea455fe56cf6cff","observation_id":"53ca7edd-7942-4d1d-b26f-1efd0d2ac11b","resolution":{"observed_at":"2026-08-10T11:26:57.706661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06647","last_updated":"2025-02-19T04:16:24Z","snapshot_observed_at":"2026-08-10T11:53:51.860158Z","submitted_at":"2024-06-10T04:19:20Z","title":"How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06647","snapshot_observed_at":"2026-08-10T11:26:57.710732Z","title":"How efficient is llm-generated code? a rigorous & high-standard benchmark,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.710732Z"},"links":{"cited_paper":"/paper/2406.06647","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:7d85a1d0ef602e03c7be9d40852977affcac3c99d238e890251b97557273850f","observation_id":"8c731b3b-1bd8-431d-bf7f-1619509f4a7a","resolution":{"observed_at":"2026-08-10T11:26:57.710732Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.14924","last_updated":"2023-06-23T20:57:32Z","snapshot_observed_at":"2026-08-07T22:03:54.164128Z","submitted_at":"2023-06-23T20:57:32Z","title":"LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Coding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.14924","snapshot_observed_at":"2026-08-10T11:26:57.715168Z","title":"Llm- assisted content analysis: Using large language models to support deductive coding,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.715168Z"},"links":{"cited_paper":"/paper/2306.14924","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:26211796310ab15ff0c19b3d73e2e3bbda493da49c1e39c591cfd34994baf3f2","observation_id":"914cf1c0-4b97-4278-a733-e9d0e8fc33d7","resolution":{"observed_at":"2026-08-10T11:26:57.715168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08837","last_updated":"2023-10-13T03:16:58Z","snapshot_observed_at":"2026-08-03T10:45:51.085583Z","submitted_at":"2023-10-13T03:16:58Z","title":"Static Code Analysis in the AI Era: An In-depth Exploration of the Concept, Function, and Potential of Intelligent Code Analysis Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08837","snapshot_observed_at":"2026-08-10T11:26:57.719599Z","title":"Static code analysis in the ai era: An in-depth exploration of the concept, function, and potential of intelligent code analysis agents,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.719599Z"},"links":{"cited_paper":"/paper/2310.08837","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:2d541f3e1bdc0303c376cf6318b0bb7745ab3a37dff087506786a7f11a893802","observation_id":"9ab82d0b-ef58-40bf-b112-0fd640466e3c","resolution":{"observed_at":"2026-08-10T11:26:57.719599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.12938","last_updated":"2023-09-22T15:37:07Z","snapshot_observed_at":"2026-07-06T16:22:26.069983Z","submitted_at":"2023-09-22T15:37:07Z","title":"Frustrated with Code Quality Issues? LLMs can Help!","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.12938","snapshot_observed_at":"2026-08-10T11:26:57.723726Z","title":"Frustrated with code quality issues? llms can help!","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.723726Z"},"links":{"cited_paper":"/paper/2309.12938","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:4488068deea2808efd441497c528dfc9cec3c108cdbb622cff1f071ffe673925","observation_id":"c56c550f-256f-4ade-8be5-9d9fedca9c01","resolution":{"observed_at":"2026-08-10T11:26:57.723726Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.727362Z","title":"Using an llm to help with code understanding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.727362Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:37bb919f642d48c079cb34ebd09972c5889ebf6cd0fc3dcd373d9dbb03b193d7","observation_id":"fa7f4c0c-3e14-4dad-8056-69bd80a5d806","resolution":{"observed_at":"2026-08-10T11:26:57.727362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.12655","last_updated":"2021-08-29T19:43:43Z","snapshot_observed_at":"2026-08-06T05:51:42.612813Z","submitted_at":"2021-05-25T00:13:29Z","title":"CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.12655","snapshot_observed_at":"2026-08-10T11:26:57.730680Z","title":"Codenet: A large- scale ai for code dataset for learning a diversity of coding tasks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.730680Z"},"links":{"cited_paper":"/paper/2105.12655","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:e77e9613282c1fc7f81499b3448ddc668dbc671d6079e845ec8d293eee3e5a56","observation_id":"f2b26859-57a6-4093-8c15-bba62602bf29","resolution":{"observed_at":"2026-08-10T11:26:57.730680Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-10T11:26:57.734290Z","title":"Gpt-4o system card,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.734290Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:f14e6ea6995431016c9572ea335ae3a49b892bce454141dd6d5e923c81387887","observation_id":"6b05382f-6abe-4e92-849c-73afbe48adec","resolution":{"observed_at":"2026-08-10T11:26:57.734290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.08155","last_updated":"2020-09-18T15:38:12Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-02-19T13:09:07Z","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08155","snapshot_observed_at":"2026-08-10T11:26:57.737906Z","title":"Codebert: A pre-trained model for programming and natural languages,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.737906Z"},"links":{"cited_paper":"/paper/2002.08155","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:dcaf95adda09e0f45bd3f5f97b86b7bc8693fcaf6ecdd1725e0370d8d67ee7a7","observation_id":"b6491a4f-bf05-4564-a579-45d32296a9be","resolution":{"observed_at":"2026-08-10T11:26:57.737906Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.437331Z","title":"Do machines and humans focus on similar code? exploring explainability of large language models in code summarization,","venue":null,"work_id":"f95c915c-e94a-48c8-b94c-5df3271fa20a","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.741882Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:10535db2e2f080f7577faec3c2ebc31659b5b59aa80a047f89b91280f6c84da1","observation_id":"cb0104ff-b3d0-443c-bce2-1810a04d3bdb","resolution":{"observed_at":"2026-08-10T11:26:58.441190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.426242Z","title":"Modeling programmer attention as scanpath prediction,","venue":null,"work_id":"d6b47503-dcfc-47af-8519-ed3109255963","year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.745288Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:c9add0f85fcb6bec4f58b0e52ff0821c8a359d4f4052f853e74c795fd1ea31c6","observation_id":"28d4b9c9-f677-4f51-8560-abd306f01f74","resolution":{"observed_at":"2026-08-10T11:26:58.429786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.416246Z","title":"Eyetrans: Merging human and machine attention for neural code summarization,","venue":null,"work_id":"ed74ced3-f871-43c1-8252-5c9a3362bee3","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.748653Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:ecee5d98bd013e3830c77616c83a4a246e9378916ad77575ac4a9b1e7043c3ee","observation_id":"21b37bf2-dc66-481c-9b11-8efc3826062c","resolution":{"observed_at":"2026-08-10T11:26:58.419798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.405006Z","title":"A tale of two comprehensions? analyzing student programmer attention during code summarization,","venue":null,"work_id":"91bd650e-6b11-41e8-aa8b-35c3c6cf4885","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.751859Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:55796efde9f5723f46d89556177e80032cebdceed940f23e6b6cde0cb077acc0","observation_id":"01857d13-d3c0-4f06-80d1-f1757e70cefd","resolution":{"observed_at":"2026-08-10T11:26:58.409383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.755198Z","title":"Pre-training representations of binary code using contrastive learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.755198Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:14ab15ffc8b2b25baf4e2ca7e028b81f77120a0d465534e0db03462be8c5e9c2","observation_id":"10b248a5-265c-48fd-9db6-fdebd0a4abfc","resolution":{"observed_at":"2026-08-10T11:26:57.755198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.394447Z","title":"Leveraging artificial intelligence on binary code comprehen- sion,","venue":null,"work_id":"24b6fffd-1f30-49cc-86d7-df67a445d08e","year":2022},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.758684Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:4c031d6c808b4c8d3100db681c6e96bbd15e3d50eca1c55d077ea7510017ff02","observation_id":"d54a3814-4c9a-4cf2-8230-82888d329f4d","resolution":{"observed_at":"2026-08-10T11:26:58.398038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.05514","last_updated":"2024-10-03T17:15:34Z","snapshot_observed_at":"2026-08-05T01:58:10.243343Z","submitted_at":"2024-06-08T16:24:24Z","title":"RAG-Enhanced Commit Message Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.05514","snapshot_observed_at":"2026-08-10T11:26:57.761898Z","title":"Rag-enhanced commit message generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.761898Z"},"links":{"cited_paper":"/paper/2406.05514","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:22914720959a9635b8f8feb2698945f326e662c83df3ff4576b685694a5a7937","observation_id":"b089cf34-51d0-442a-aaac-35af9bb8acce","resolution":{"observed_at":"2026-08-10T11:26:57.761898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07530","last_updated":"2024-05-13T07:56:15Z","snapshot_observed_at":"2026-08-09T18:51:47.242584Z","submitted_at":"2024-05-13T07:56:15Z","title":"Prompt-based Code Completion via Multi-Retrieval Augmented Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07530","snapshot_observed_at":"2026-08-10T11:26:57.764927Z","title":"Prompt-based code completion via multi-retrieval augmented genera- tion,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.764927Z"},"links":{"cited_paper":"/paper/2405.07530","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:36bb49f8bb7f1089c521f7c15f5ff3bc321afabcde4d1e625fb6fa309cdd3e75","observation_id":"a8f28cff-0a28-40e2-9f46-3c1e5874e77f","resolution":{"observed_at":"2026-08-10T11:26:57.764927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.383648Z","title":"Evaluating retrieval-augmented generation (rag) tech- niques in enhancing lms for coding tasks,","venue":null,"work_id":"a2cb7f2d-193f-4f1b-b146-94d834abeea6","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.768157Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:e475d80e1a017f843389f3d97fa916ab9e067aac6f14a3685b8802b019918a49","observation_id":"6a60e9fe-7fe2-492b-8f13-bdefb502922a","resolution":{"observed_at":"2026-08-10T11:26:58.387434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.13213","last_updated":"2025-04-17T17:51:35Z","snapshot_observed_at":"2026-07-06T19:18:32.034335Z","submitted_at":"2024-09-20T04:50:49Z","title":"MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning","version":4},"cited_work":{"arxiv_id":"2409.13213","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.13213","snapshot_observed_at":"2026-08-10T11:26:57.943538Z","title":"MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning","venue":"cs.CR","work_id":"48017b7d-7a40-4e1f-b03f-5f34102f0e4f","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.770810Z"},"links":{"cited_paper":"/paper/2409.13213","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:b82214b7e427d1194f27ff29341746e8dd305b37c4194f0ae7c2edac0f26b733","observation_id":"73424439-8803-40fc-bcd1-3c420d978c51","resolution":{"observed_at":"2026-08-10T11:26:57.949653Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.19619","last_updated":"2024-07-29T00:41:48Z","snapshot_observed_at":"2026-08-10T05:39:42.812138Z","submitted_at":"2024-07-29T00:41:48Z","title":"Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.19619","snapshot_observed_at":"2026-08-10T11:26:57.773967Z","title":"Enhancing code translation in language models with few-shot learning via retrieval-augmented generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.773967Z"},"links":{"cited_paper":"/paper/2407.19619","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:ada40c5b57cc18d5aae95fb676c043ea185500ffff4631d4df6ab606811e2b10","observation_id":"e0cd5785-91bb-4434-ae21-504cb702b43a","resolution":{"observed_at":"2026-08-10T11:26:57.773967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.12317","last_updated":"2024-12-03T15:56:26Z","snapshot_observed_at":"2026-07-06T17:32:19.965690Z","submitted_at":"2024-02-19T17:37:28Z","title":"EVOR: Evolving Retrieval for Code Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.12317","snapshot_observed_at":"2026-08-10T11:26:57.777197Z","title":"Arks: Active retrieval in knowledge soup for code generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.777197Z"},"links":{"cited_paper":"/paper/2402.12317","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:65735f76c5527fbd0b7f9a0bbf5da0b2f520cadc330f7ced01455524e7e91e57","observation_id":"8f83f313-ad5e-42b3-948b-b1685c670e2a","resolution":{"observed_at":"2026-08-10T11:26:57.777197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14497","last_updated":"2025-02-26T22:10:36Z","snapshot_observed_at":"2026-07-06T18:34:24.078145Z","submitted_at":"2024-06-20T16:59:52Z","title":"CodeRAG-Bench: Can Retrieval Augment Code Generation?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14497","snapshot_observed_at":"2026-08-10T11:26:57.780507Z","title":"Coderag-bench: Can retrieval augment code generation?","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.780507Z"},"links":{"cited_paper":"/paper/2406.14497","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:649e9f6011cad767bcbb95f7eb14a59b3e6b98b0c912ee0bef2e3cdae597ebee","observation_id":"530ba084-3712-4476-8208-766584fc33aa","resolution":{"observed_at":"2026-08-10T11:26:57.780507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.783723Z","title":"Llm-based and retrieval-augmented control code generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.783723Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:d4b865f2d5e8fa2ca67789f1aba9b2679767f68a1f15c37a212295871ca4decd","observation_id":"d089230e-6df4-4340-9252-fce46def9a32","resolution":{"observed_at":"2026-08-10T11:26:57.783723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.786962Z","title":"A survey on rag meeting llms: Towards retrieval-augmented large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.786962Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:000cd500924ccc52974d1e723df19ff10531398932691ae40f75572806103237","observation_id":"855eaf32-d694-40a6-8b76-edc364de9bb1","resolution":{"observed_at":"2026-08-10T11:26:57.786962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.19473","last_updated":"2024-06-21T08:26:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-29T18:59:01Z","title":"Retrieval-Augmented Generation for AI-Generated Content: A Survey","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.19473","snapshot_observed_at":"2026-08-10T11:26:57.790111Z","title":"Retrieval-augmented generation for ai-generated content: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.790111Z"},"links":{"cited_paper":"/paper/2402.19473","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:f4582715564e93a5704f0a1d0fced36db4662c5378fc914a80ad35e84238bfaf","observation_id":"2fa9b542-1d8d-4ab3-bba5-d307acd02977","resolution":{"observed_at":"2026-08-10T11:26:57.790111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.793716Z","title":"What makes good examples for visual in-context learning?","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.793716Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:11ec9e1fdf5c09a21023233d0e81b3bd61748c0394df5ecfef5843ab08b93411","observation_id":"d1988903-7601-438e-8a5d-36390cde1f7e","resolution":{"observed_at":"2026-08-10T11:26:57.793716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.355351Z","title":"The learnability of in-context learning,","venue":null,"work_id":"e3a41f5a-de3f-45b4-b7f8-8db37360d3d4","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.796865Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:1b87a2597eb8c543efda40d46077e2e5dcf0ebcf41ee750e45df74bb786bafc6","observation_id":"6e29aab4-62c6-428f-9adb-d6ab72c1910c","resolution":{"observed_at":"2026-08-10T11:26:58.358795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.799975Z","title":"Compositional exemplars for in-context learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.799975Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:03c27981817accc7ceed1a45ab58529dff46d5cc7e07e587fda3c94ab49829d3","observation_id":"9924fd90-9246-48ce-b8c7-76dd6ec456fc","resolution":{"observed_at":"2026-08-10T11:26:57.799975Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13539","last_updated":"2023-10-09T02:39:04Z","snapshot_observed_at":"2026-08-10T11:50:44.376019Z","submitted_at":"2023-02-27T06:32:45Z","title":"Finding Support Examples for In-Context Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13539","snapshot_observed_at":"2026-08-10T11:26:57.803071Z","title":"Finding support examples for in-context learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.803071Z"},"links":{"cited_paper":"/paper/2302.13539","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:880534c6c215282afa59153d25c4c97df4f16cec935d8c56e108558ef35e5660","observation_id":"a021b10a-0455-4b6d-a7c4-416b66c592ca","resolution":{"observed_at":"2026-08-10T11:26:57.803071Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.00865","last_updated":"2025-03-22T05:52:26Z","snapshot_observed_at":"2026-08-11T05:35:29.041833Z","submitted_at":"2024-10-30T19:45:50Z","title":"Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.00865","snapshot_observed_at":"2026-08-10T11:26:57.806487Z","title":"Democraft: Using in-context learning to improve code generation in large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.806487Z"},"links":{"cited_paper":"/paper/2411.00865","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:d1a155ce616a649e41b24b60f8e23eaed626a4666b38cd2cf3f83470687bf6bb","observation_id":"c771b63e-d2ec-4cc6-84e0-8e204cb6e895","resolution":{"observed_at":"2026-08-10T11:26:57.806487Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07579","last_updated":"2024-06-06T06:31:08Z","snapshot_observed_at":"2026-07-06T16:31:16.784700Z","submitted_at":"2023-10-11T15:19:31Z","title":"In-Context Unlearning: Language Models as Few Shot Unlearners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07579","snapshot_observed_at":"2026-08-10T11:26:57.809808Z","title":"In-context unlearning: Lan- guage models as few shot unlearners,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.809808Z"},"links":{"cited_paper":"/paper/2310.07579","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:a68efce13d182db0e2876699663791dd69b06aaa9c75dcb541955a3d6845e64d","observation_id":"717425e1-96bf-45e6-a91c-13eb620177ea","resolution":{"observed_at":"2026-08-10T11:26:57.809808Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:58.339505Z","title":"Evaluating the effectiveness of deep learning models for foundational program analysis tasks,","venue":null,"work_id":"89f55a36-e014-435f-9c11-0125ed523513","year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.813278Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:dd6c6ff14d3009497264ed013a306fee365b82f1406245f7d78beda623e1a0a0","observation_id":"4af7f9ee-5c79-4e30-878c-0714bbc93380","resolution":{"observed_at":"2026-08-10T11:26:58.342588Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.816366Z","title":"Enchanting program specification synthesis by large language models using static analysis and program verification,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.816366Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:f5abdd260cc75b145d47baa4b95249319eae1bbf9e96538be6a05c61da35367b","observation_id":"2f9c788f-9d34-45b9-ae83-cc596946169f","resolution":{"observed_at":"2026-08-10T11:26:57.816366Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06439","last_updated":"2024-12-11T21:52:23Z","snapshot_observed_at":"2026-08-10T17:21:58.626858Z","submitted_at":"2023-05-10T20:14:52Z","title":"Measuring the Runtime Performance of C++ Code Written by Humans using GitHub Copilot","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06439","snapshot_observed_at":"2026-08-10T11:26:57.819619Z","title":"Mea- suring the runtime performance of code produced with github copilot,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.819619Z"},"links":{"cited_paper":"/paper/2305.06439","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:b958d21a0696c9c0dc5e3cff664eba8d608af4414fd260e630bcde3d33cdc02b","observation_id":"b44e91bc-2c0f-4ecf-be9b-b3c2a3049989","resolution":{"observed_at":"2026-08-10T11:26:57.819619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.822973Z","title":"Detecting code comment inconsistencies using llm and program analysis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.822973Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:149b044644ca7bdb7a9090c5e617dffe221f3409e7c9f091ee3115a8cd0a21b7","observation_id":"856c888f-ca99-42ba-9a52-3f0d32c44e11","resolution":{"observed_at":"2026-08-10T11:26:57.822973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T11:26:57.826026Z","title":"Codeplan: Repository-level coding using llms and planning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.826026Z"},"links":{"citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:80be088eef05be9b895de33100a7a04237fb9ba6f2eba42aa957f8e7d5548563","observation_id":"018d256f-5ab8-41ec-8426-965b942cbb50","resolution":{"observed_at":"2026-08-10T11:26:57.826026Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.13642","last_updated":"2025-03-19T04:22:52Z","snapshot_observed_at":"2026-08-06T17:52:16.299355Z","submitted_at":"2024-09-20T16:47:34Z","title":"A Multi-Agent Approach to Fault Localization via Graph-Based Retrieval and Reflexion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.13642","snapshot_observed_at":"2026-08-10T11:26:57.829198Z","title":"Enhancing fault localization through ordered code analysis with llm agents and self- reflection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T11:26:57.829198Z"},"links":{"cited_paper":"/paper/2409.13642","citing_paper":"/paper/2501.16692"},"observation_digest":"sha256:05c1dd944397407f4526845d1b3f5108df66b86cebff675ce78bb44a0a1415d9","observation_id":"b9de8837-8944-4c3a-8b9e-f0372e842ffd","resolution":{"observed_at":"2026-08-10T11:26:57.829198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.16692","last_updated":"2025-01-29T04:36:03Z","latest_version":2,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-10T11:50:57.483842Z","submitted_at":"2025-01-28T04:00:35Z","title":"Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":29,"verified_exact":2,"verified_fuzzy":9},"total_outbound_references":40},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 2 inbound Pith citation observations for arXiv:2501.16692."}