{"as_of":"2026-08-08T10:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:269d314894a615264e7fbce6192b2ab808e019f028e56fe5973353e3040bf99c","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T06:00:22.680773Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.06227/citation-record","integrity":"/paper/2506.06227/integrity","json":"/paper/2506.06227/citation-record.json","paper":"/paper/2506.06227"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.931252Z","title":"[Accessed 15-05-2025]","venue":null,"work_id":"63c6a522-1d6a-4869-91eb-a9aa1ae64a37","year":2025},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.609799Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:3ae3098de2ba12ca44af6aaf4450025ff24f53b347542110d33f273902a56d5a","observation_id":"ea0bf972-fb7e-437e-bbab-bc1b3d5c6886","resolution":{"observed_at":"2026-08-07T06:00:22.935249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.918369Z","title":"[Accessed 15-05-2025]","venue":null,"work_id":"701503ac-00a0-45be-85d8-78a634fb909e","year":2025},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.614673Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:32f8175ed103a853e191ef9d2e0d18e23e1a952a8336c54656b2c05fed0f4b74","observation_id":"2c52cb1f-9b69-4a0b-a7d2-67f11aa2b74c","resolution":{"observed_at":"2026-08-07T06:00:22.922396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.905606Z","title":"[Accessed 15-05-2025]","venue":null,"work_id":"36be088d-08c1-466a-803e-550854e0628b","year":2025},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.619653Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:6cf3deb70d295f0fccd1f3de7287474065397e85a865142cd3e9406d15353644","observation_id":"658c593e-85f6-43a3-88bd-642de0c21591","resolution":{"observed_at":"2026-08-07T06:00:22.909668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.892589Z","title":"Cognition | Introducing Devin, the first AI software engineer — cognition.ai.https: //www.cognition.ai/blog/introducing-devin","venue":null,"work_id":"1882dfcc-91ed-49c2-84d9-478a5434584d","year":2025},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.623926Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:b64b03b2016b69b51036e7619b3c6646f6361c64b8ac5653db39ea539639715a","observation_id":"7dd36ce7-a2ae-4635-89dd-0670866f29fa","resolution":{"observed_at":"2026-08-07T06:00:22.897165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.07062","last_updated":"2023-09-11T22:11:46Z","snapshot_observed_at":"2026-08-04T14:17:17.034755Z","submitted_at":"2023-09-11T22:11:46Z","title":"Large Language Models for Compiler Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.07062","snapshot_observed_at":"2026-08-07T06:00:22.628831Z","title":"Large language models for compiler optimization.arXiv preprint arXiv:2309.07062, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.628831Z"},"links":{"cited_paper":"/paper/2309.07062","citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:caab8ad292a4d93918bef9e474a1a76eb083427dae62de94e55dbc4ab282af47","observation_id":"64ddd096-d934-4949-8c50-cfae63c7d4c9","resolution":{"observed_at":"2026-08-07T06:00:22.628831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02524","last_updated":"2024-06-27T21:47:48Z","snapshot_observed_at":"2026-08-07T04:21:00.702063Z","submitted_at":"2024-06-27T21:47:48Z","title":"Meta Large Language Model Compiler: Foundation Models of Compiler Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.02524","snapshot_observed_at":"2026-08-07T06:00:22.633715Z","title":"Meta large language model compiler: Foundation models of compiler optimization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.633715Z"},"links":{"cited_paper":"/paper/2407.02524","citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:a8fd187de97c29d4280052d06eacb914453c2d94fe1dacd8832136dc91b8d6d9","observation_id":"2b34d81a-dd7b-4c08-b539-1cba768ea646","resolution":{"observed_at":"2026-08-07T06:00:22.633715Z","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":"2026-08-07T06:00:22.879451Z","title":"Faros: A frame- work to analyze openmp compilation through benchmarking and compiler optimization analysis","venue":null,"work_id":"9d83b755-07de-4276-ac78-b1f15f18e678","year":2020},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.638787Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:06a765f722ca20fc3f74b29a614c7901d9d11c4e64e4a23e3c067cc4c3c3668d","observation_id":"7e80b7af-482b-4eaa-9451-c6f42dff83bb","resolution":{"observed_at":"2026-08-07T06:00:22.883991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.864824Z","title":"Large language models for software engineering: A systematic literature review.ACM Transactions on Software Engineering and Methodology, 2023","venue":null,"work_id":"8504c6a1-c32d-4370-a8f4-327a9c468689","year":2023},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.642842Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:b18b3a6a7a2d084ec0df2575c7f6ff384ec1f4f07ea5acc7a9eb439f822f0513","observation_id":"0af9c7f1-0f32-47f2-a522-43c777fd3066","resolution":{"observed_at":"2026-08-07T06:00:22.869536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.849554Z","title":"The openmp implementation of nas parallel bench- marks and its performance","venue":null,"work_id":"75eb2821-e967-4335-956f-7d807f907434","year":1999},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.646859Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:1a9192a5d932d450e5e8c66bd395c3b76e74af8c6de46696d1d4e80b4657d24c","observation_id":"dd1f4fc1-056f-4f36-b535-eaa5469625fd","resolution":{"observed_at":"2026-08-07T06:00:22.853914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.836491Z","title":"A comparison of the effectiveness of chatgpt and co-pilot for generating quality python code solutions","venue":null,"work_id":"cd4afddf-5ba4-4c1d-99c0-8b08592e9acf","year":2024},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.650887Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:2d03ebdc32d4d271e76f2108b974f947871d5266e7611f3812908fd1af8290fc","observation_id":"a0a66175-7692-4d68-b627-795c868e128e","resolution":{"observed_at":"2026-08-07T06:00:22.840738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.823014Z","title":"Navigating compiler errors with ai assistance-a study of gpt hints in an introductory programming course","venue":null,"work_id":"65ae19d3-ee26-4f08-8124-cd61fc5494a9","year":2024},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.654859Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:912ef366343c2785b2c7da1e886b37d2982d63d6fb1e7a8f04168ff0ff0993d9","observation_id":"03772895-5cc9-48bd-b95d-e8daaf7ccc85","resolution":{"observed_at":"2026-08-07T06:00:22.827445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.808057Z","title":"Identification of common molecular subsequences.Journal of molecular biology, 147(1):195–197, 1981","venue":null,"work_id":"cdea8e51-12a6-4532-872d-98f1ba9d9a97","year":1981},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.658738Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:d57c4f5f991b0cc94b742a04d59b1cbe1b5396d0a1e05c0966bf5474247639ae","observation_id":"c934a8e5-e267-4939-bd26-160461a143f1","resolution":{"observed_at":"2026-08-07T06:00:22.813159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T06:00:22.792456Z","title":"Dcc–help: Transforming the role of the compiler by generating context-aware error explanations with large language models","venue":null,"work_id":"00aadc0d-521c-444b-b1b3-d0a79a96464c","year":2024},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.662591Z"},"links":{"citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:e76d2e09dfd6b6a01f90bb53aa0d52b4aa41731c0362ad1660c7a9b707e87e8a","observation_id":"ed62b8be-6161-4dd1-937b-654d1fc1f1a5","resolution":{"observed_at":"2026-08-07T06:00:22.798370Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16741","last_updated":"2025-04-18T18:14:31Z","snapshot_observed_at":"2026-08-02T14:58:44.167588Z","submitted_at":"2024-07-23T17:50:43Z","title":"OpenHands: An Open Platform for AI Software Developers as Generalist Agents","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.16741","snapshot_observed_at":"2026-08-07T06:00:22.666850Z","title":"Openhands: An open platform for ai software developers as generalist agents.arXiv preprint arXiv:2407.16741, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.666850Z"},"links":{"cited_paper":"/paper/2407.16741","citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:df3f91b5132988b32d44b30bacef1fee2c3c94518f942391cc838eb368739a26","observation_id":"4e202665-ff3e-4de8-9cc3-9b553b5d9a50","resolution":{"observed_at":"2026-08-07T06:00:22.666850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.10793","last_updated":"2023-07-20T11:46:48Z","snapshot_observed_at":"2026-08-07T22:00:49.278349Z","submitted_at":"2023-07-20T11:46:48Z","title":"Addressing Compiler Errors: Stack Overflow or Large Language Models?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.10793","snapshot_observed_at":"2026-08-07T06:00:22.670984Z","title":"Addressing compiler errors: Stack overflow or large language models?arXiv preprint arXiv:2307.10793, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.670984Z"},"links":{"cited_paper":"/paper/2307.10793","citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:014e386bca0998d64147ba9b97de64df0c54c0dd78235cd7323b9a975457a4c5","observation_id":"fb327108-fc36-49b4-b034-d6e973f9d9ac","resolution":{"observed_at":"2026-08-07T06:00:22.670984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.15793","last_updated":"2024-11-11T20:01:15Z","snapshot_observed_at":"2026-07-06T18:19:29.996982Z","submitted_at":"2024-05-06T17:41:33Z","title":"SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.15793","snapshot_observed_at":"2026-08-07T06:00:22.676692Z","title":"Swe-agent: Agent-computer interfaces enable automated software engineering.arXiv preprint arXiv:2405.15793, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.676692Z"},"links":{"cited_paper":"/paper/2405.15793","citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:ba4dd9c41ce1fa41373da1005aefd2956ea1b69bc582e44df4b2da0bf19e2495","observation_id":"8337bcba-5f89-46dd-9afc-f5c584522628","resolution":{"observed_at":"2026-08-07T06:00:22.676692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05687","last_updated":"2023-09-11T16:39:37Z","snapshot_observed_at":"2026-07-06T16:17:04.004519Z","submitted_at":"2023-09-11T16:39:37Z","title":"Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05687","snapshot_observed_at":"2026-08-07T06:00:22.680773Z","title":"Demystifyingpractices, challenges and expected features of using github copilot.arXiv preprint arXiv:2309.05687, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T06:00:22.680773Z"},"links":{"cited_paper":"/paper/2309.05687","citing_paper":"/paper/2506.06227"},"observation_digest":"sha256:047eb23928c49d72b1d530750c8fbccd16dcccaced73e03ef1323f53d8893357","observation_id":"03b259bc-e970-47a4-ab82-5eb7b3e537b1","resolution":{"observed_at":"2026-08-07T06:00:22.680773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.06227","last_updated":"2025-06-12T18:56:51Z","latest_version":2,"primary_category":"cs.PL","snapshot_observed_at":"2026-08-07T05:55:57.121535Z","submitted_at":"2025-06-06T16:42:14Z","title":"CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":17},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2506.06227."}