{"as_of":"2026-08-16T16:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2c20af30a0cf9cab74cdf5b5b9aabe658fa78c2dcee5ac615bf60c4ae9193902","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T14:13:50.047565Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/2412.12340/citation-record","integrity":"/paper/2412.12340/integrity","json":"/paper/2412.12340/citation-record.json","paper":"/paper/2412.12340"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T14:13:50.505515Z","title":"Taming timeout flakiness: An empirical study of sap hana,","venue":null,"work_id":"4173086c-572a-4892-97f3-c8b41032fae6","year":2024},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.893672Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:b57b6f27f49e0b477f31319cdd0ac27ae041f18aa32a855de947c9bfa0e0699f","observation_id":"45b16767-f076-434a-9ec4-3e411e2541c5","resolution":{"observed_at":"2026-08-11T14:13:50.508934Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.495545Z","title":"Software testing research challenges: An industrial perspective,","venue":null,"work_id":"59cbf771-7e1e-4f18-9525-460e8361b6d2","year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.898263Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:376065d9c10f78dae534d097b4519f40e7914b368d41dd63f16c329fa8e91706","observation_id":"c0d809a6-b80e-4e73-a624-fe3ee458160a","resolution":{"observed_at":"2026-08-11T14:13:50.499099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.484625Z","title":"Deflaker: Automatically detecting flaky tests,","venue":null,"work_id":"4e9a7114-94dd-46e7-b2a0-c11a1583d241","year":2018},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.902223Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:7852326c7a11dceb486361b5e8300b3aaf25e26e50a1f6c948cb09f298445ae4","observation_id":"a62b35c6-db09-43ca-b7b3-a61e5621335b","resolution":{"observed_at":"2026-08-11T14:13:50.489270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.474153Z","title":"De-flake your tests: Automatically locating root causes of flaky tests in code at google,","venue":null,"work_id":"344c026d-b056-4481-80da-ddaf9b1eadf9","year":2020},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.906239Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:f316087384daa724d89ed915df567e745c9664e7369c983592d855d9891f9f0b","observation_id":"5766d0c8-aab0-46f1-b673-32ac286bc1ab","resolution":{"observed_at":"2026-08-11T14:13:50.477829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.463692Z","title":"What do developer -repaired flaky tests tell us about the effective ness of automated flaky test detection?,","venue":null,"work_id":"a508b011-7f4a-4104-9bef-beea395d919c","year":2022},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.910045Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:9e596f7e0730ad4e988b433b274412568c36053b4738fff09558ce236306946b","observation_id":"d607fe4a-9f41-41a6-a5a6-756e53ec8ed2","resolution":{"observed_at":"2026-08-11T14:13:50.467699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.452577Z","title":"A multi -factor approach for flaky test detection and automated root cause analysis,","venue":null,"work_id":"985ed187-f3d8-4c41-8e71-ae8df38c9d12","year":2021},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.914847Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:a60dcc5b79d3c5541ec07ca272d6043eedf8b3abb217a5f71a4d41b6d970294a","observation_id":"ab32545d-9088-41f0-aa32-1caf22788bff","resolution":{"observed_at":"2026-08-11T14:13:50.456493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.442129Z","title":"Flakycat: predicting flaky tests categories using few-shot learning,","venue":null,"work_id":"75187395-084e-4c6f-9ac7-34b3e2371bf7","year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.920206Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:497e0e59f0399eeca869944f9d4a1352f66aff6dcc19965ee6f9836b8494a413","observation_id":"8375aef0-ecad-423c-bdec-1c9a6dd96cb9","resolution":{"observed_at":"2026-08-11T14:13:50.446361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.431383Z","title":"Continuous practices and devops: beyond the buzz, what does it all mean?,","venue":null,"work_id":"a77b3757-31c2-42c2-a0f4-de328e790133","year":2017},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.924045Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:1798eceef8700aa4cd312885c29cf84324c4e806a81972c5baf3643759bd3f71","observation_id":"06135752-7c71-4c19-99d5-37d8c9763fe2","resolution":{"observed_at":"2026-08-11T14:13:50.435043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.421860Z","title":"A qualitative study on the sources, impacts, and mitigation strategies of fla ky tests,","venue":null,"work_id":"9abc0201-46a8-4a1f-bf87-10539e9de38e","year":2022},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.927568Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:be3888ccd4a7d0c4690dd1ad76e5fd569c6a6eed13d79a4e7d88b9bb32eb6146","observation_id":"1127c986-34b3-4215-99d1-c5fc443c64af","resolution":{"observed_at":"2026-08-11T14:13:50.425056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.412389Z","title":"Understanding flaky tests: The developer’s perspective,","venue":null,"work_id":"8cd80eb0-61ab-4308-a9c7-309b6f043830","year":2019},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.931163Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:2b237cdd15ad985d148653502e1758166fb36341c6613e6cd6dce9a8f8230c90","observation_id":"a51adb9a-fd34-417b-bd79-42750da0096e","resolution":{"observed_at":"2026-08-11T14:13:50.416018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.401943Z","title":"Taming google-scale continuous testing,","venue":null,"work_id":"5aff6112-6c68-41aa-8dbd-af655c0f79e2","year":2017},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.934662Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:766936692e2b5bd1627a260fa3a79d69db538d5af2caae3d66ee6cd83baf0b10","observation_id":"7c1af11d-cc88-42dd-8d1a-87589ae24624","resolution":{"observed_at":"2026-08-11T14:13:50.405925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.391918Z","title":"Root causing flaky tests in a large-scale industrial setting,","venue":null,"work_id":"dd55e51c-d92b-41fe-b47c-65570ca97889","year":2019},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.938425Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:b9ced4706919fee3f7bcf8865774041c5be52e01fcf7f10ee6175c05d6d81fb0","observation_id":"27c70ad6-15cb-4781-a947-c669f23a5356","resolution":{"observed_at":"2026-08-11T14:13:50.395517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.381719Z","title":"A survey of flaky tests,","venue":null,"work_id":"0af49916-13ca-451e-8990-3d9850cffca3","year":2021},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.941208Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:3dde768fd9cf973d9d4f9c6f9516edce505917fd654536b5dcd676bcf0f981e9","observation_id":"1786ba43-1bf8-4190-bc97-46b3b3e47ea5","resolution":{"observed_at":"2026-08-11T14:13:50.385307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.371646Z","title":"A survey on how test flakiness affects developers and what support they need to address it,","venue":null,"work_id":"83eef81f-6d0e-4496-81ad-c481523ecebf","year":2022},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.943971Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:8ec79b79721d6ac88dbd53440003a4bd0f337801f03901be1890ea230fb1a4da","observation_id":"ec6066da-b138-4f39-846f-a549c671ec83","resolution":{"observed_at":"2026-08-11T14:13:50.375335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.362008Z","title":"Shake it! detecting flaky tests caused by concurrency with shaker,","venue":null,"work_id":"b77f5ae5-a645-4df1-9be5-61198773ab0e","year":2020},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.946892Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:9ddb73b2dea191c681e03a35693717b830a7a32ef2c70fe3f938753f936c2fc2","observation_id":"a4b849d9-054d-4551-bd83-c876bd668b65","resolution":{"observed_at":"2026-08-11T14:13:50.365334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.352933Z","title":"iDFlakies: A framework for detecting and partially classifying flaky tests,","venue":null,"work_id":"97145014-a87f-48a4-90f7-8f07f46e892b","year":2019},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.950985Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:aa934c9d341c18275d1878d3b8c5c93c68dd8fc2777da8cc72482ed09eeae31e","observation_id":"c218e360-22e3-4bf3-8562-4169f4527a8f","resolution":{"observed_at":"2026-08-11T14:13:50.356037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.343298Z","title":"Empirically revisiting the test independence assumption,","venue":null,"work_id":"c3fbed86-fa0f-42f1-8752-fd61b6e57f47","year":2014},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.954269Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:9118cd5542d331ec45d22e8299cffb30d4d8dfdba46787147834dd292573535c","observation_id":"46b6a9cf-8930-45b9-987b-eb2f2fa1b8fc","resolution":{"observed_at":"2026-08-11T14:13:50.346865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.332059Z","title":"What is the vocabulary of flaky tests?,","venue":null,"work_id":"787a1dc3-a3ba-4398-80f0-e7eb47b4b1fd","year":2020},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.957812Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:cf496a90dd6c2a075fee98d956531102266f110332eaf437ed4f2ef5943c7625","observation_id":"d8a6e5cd-7f42-4a1f-b039-227ad8686dd4","resolution":{"observed_at":"2026-08-11T14:13:50.336280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.320920Z","title":"Towards a bayesian netwo rk model for predicting flaky automated tests,","venue":null,"work_id":"d17e277c-abaf-4322-b669-376e8d3ffb5e","year":2018},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.961138Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:1f16fef0809001a7520b20da9b17a4f65b25a5a245a05ec944c8fa79d181afda","observation_id":"f81427e8-065a-488f-950a-4cd5544b9637","resolution":{"observed_at":"2026-08-11T14:13:50.324869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.310666Z","title":"An empirical analysis of flaky tests,","venue":null,"work_id":"9c6674d9-4d2b-4db3-8444-12682085dafa","year":2014},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.965253Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:87f27182b7f8148dc8689ac601b9cd0b093d4bc38b9f4bbcf0692b31d89cf1d6","observation_id":"09abe0ad-d71f-41cf-8965-3b5635506424","resolution":{"observed_at":"2026-08-11T14:13:50.314387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.299825Z","title":"An empirical study of c++ vulnerabilities in crowd-sourced code examples,","venue":null,"work_id":"630f5930-43af-4245-965f-c17e1884fcef","year":2019},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.968756Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:fdf424249d2d81b32fe4c1ebe1c0f6097bc8d695a2cc06a73d8359b8d2dcfdee","observation_id":"9338c079-fbdd-4c1a-a5dc-299b6813bf81","resolution":{"observed_at":"2026-08-11T14:13:50.303700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11910","last_updated":"2025-04-01T07:37:55Z","snapshot_observed_at":"2026-08-16T14:17:27.106855Z","submitted_at":"2024-02-19T07:50:54Z","title":"Enhancing Large Language Models for Text-to-Testcase Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11910","snapshot_observed_at":"2026-08-11T14:13:49.972917Z","title":"Enhancing large language models for text-to-testcase generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.972917Z"},"links":{"cited_paper":"/paper/2402.11910","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:31c56dcbb4b2416535ab60799fc30856f15bae02a7f7e6f62a4057952b4696ea","observation_id":"0a67cb4f-1f1b-4f14-bc48-88df992344d9","resolution":{"observed_at":"2026-08-11T14:13:49.972917Z","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":"2026-08-11T14:13:50.288532Z","title":"Summary of chatgpt-related research and perspective towards the future of large language models,","venue":null,"work_id":"ff7bfd7f-e7c3-4ebd-b25a-bdd83c3ddbde","year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.977041Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:e8b57cb9556fa1fbf84ad07d2d18a864b7bb26ec0b521045bfd089a595b34f97","observation_id":"403549ef-fa3e-46ba-8fa3-54e3108cd659","resolution":{"observed_at":"2026-08-11T14:13:50.292354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.00859","last_updated":"2021-09-02T12:21:06Z","snapshot_observed_at":"2026-08-15T23:44:55.691307Z","submitted_at":"2021-09-02T12:21:06Z","title":"CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.00859","snapshot_observed_at":"2026-08-11T14:13:49.981168Z","title":"Codet5: Identifier -aware unified pre -trained encoderdecoder models for code understanding and generation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.981168Z"},"links":{"cited_paper":"/paper/2109.00859","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:3f8f9eafcc13a1d97530b980d0ddea6d2cb54127dfec2864d171bc2ac2b9f69b","observation_id":"299bc430-50f5-4228-ad4c-2e2d3dac5ff8","resolution":{"observed_at":"2026-08-11T14:13:49.981168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.04207","last_updated":"2024-05-19T08:51:14Z","snapshot_observed_at":"2026-08-16T15:35:01.249020Z","submitted_at":"2023-05-07T07:17:08Z","title":"No More Manual Tests? Evaluating and Improving ChatGPT for Unit Test Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.04207","snapshot_observed_at":"2026-08-11T14:13:49.984869Z","title":"No more manual tests? evaluating and improving chatgpt for unit test generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.984869Z"},"links":{"cited_paper":"/paper/2305.04207","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:07cb55dbc6f8857643047bbc2dd83f63d425720fca6e2a958d18e0e2be81c886","observation_id":"144715c7-5b5e-42ab-bc4c-6c8b21b9ac17","resolution":{"observed_at":"2026-08-11T14:13:49.984869Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.04764","last_updated":"2024-05-07T09:08:13Z","snapshot_observed_at":"2026-08-16T15:34:45.655305Z","submitted_at":"2023-05-08T15:12:07Z","title":"ChatUniTest: A Framework for LLM-Based Test Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.04764","snapshot_observed_at":"2026-08-11T14:13:49.988856Z","title":"Chatunitest: a chatgpt -based automated unit test generation tool,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.988856Z"},"links":{"cited_paper":"/paper/2305.04764","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:3718a7b516ca83fc60f34124aef42393ab1fdaf6d8fa7869d00d144dc6f01c2a","observation_id":"0ef48385-1839-4a22-a03a-7d700d491f2b","resolution":{"observed_at":"2026-08-11T14:13:49.988856Z","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":"2026-08-11T14:13:50.277868Z","title":"Chapter 7 - learning to weight similarity measures with siamese networks: a case study on optimum -path forest,","venue":null,"work_id":"c9322ab5-5163-4b97-8515-5c0d05992662","year":2022},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.992694Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:cd83c0651ba30091a69f727d4cd563a7fd5bd2cfba361dbbc64a8c95ec4a99c9","observation_id":"684428c1-f988-468e-a094-7058091f2c39","resolution":{"observed_at":"2026-08-11T14:13:50.281512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.00012","last_updated":"2024-08-30T22:49:32Z","snapshot_observed_at":"2026-08-16T15:22:07.587443Z","submitted_at":"2023-06-21T19:34:16Z","title":"FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test Code Repair","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.00012","snapshot_observed_at":"2026-08-11T14:13:49.996288Z","title":"Black -box prediction of flaky test fix categories using language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:49.996288Z"},"links":{"cited_paper":"/paper/2307.00012","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:512e5d6533f55c1352925751d46ce3bd6e4b8441b374c0e8a1955ee7a65669d0","observation_id":"e8a7968e-a5bb-4ef5-8e77-2ce6b29597d3","resolution":{"observed_at":"2026-08-11T14:13:49.996288Z","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":"2026-08-11T14:13:50.267450Z","title":"Data augmentation using pre -trained transformer models,","venue":null,"work_id":"04ddc849-bb00-469c-bd08-2abdeb6e666a","year":2020},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.000359Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:113ecb0a15e6e621d74f05da37aa3a9438ab47c05516ea6fd121ca52727c8258","observation_id":"2fd3160c-bf78-4799-8ff3-9663bb5b5c17","resolution":{"observed_at":"2026-08-11T14:13:50.271377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.257191Z","title":"Learning data manipulation for augmentation and weighting,","venue":null,"work_id":"7ea8e693-f732-482e-9b7f-4d01d64a0f73","year":2019},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.003977Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:cf492fee22fecc8963f60ed841755060db500f0e5614948bcf6c90fb7743eb37","observation_id":"bab2dad4-fe8d-4db2-89bc-553a73d20460","resolution":{"observed_at":"2026-08-11T14:13:50.260845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-11T14:13:50.006935Z","title":"Gpt-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.006935Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:7ba18a9042d10edf5f0f8abf1a1042ee243484becab4b29ff8518c23e7bdafa1","observation_id":"754f6750-1714-4650-9577-72c4c260746b","resolution":{"observed_at":"2026-08-11T14:13:50.006935Z","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":"2026-08-11T14:13:50.246801Z","title":"Smote: synthetic minority oversampling technique,","venue":null,"work_id":"479325e8-026b-4374-88a8-2a56c44ddb55","year":2002},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.010148Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:99614d799b5adcd1b8bd4b2c4d06fa8c945a1efa5929ddcce2e5abc41c9b609a","observation_id":"b49edf38-18a6-4539-8eaf-14bd5e773016","resolution":{"observed_at":"2026-08-11T14:13:50.250455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.235497Z","title":"Test flakiness across programming languages,","venue":null,"work_id":"f80a9e40-a671-4e89-b871-9c7d7405305a","year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.013550Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:2594c9dd0b3f6ffc3d790a0ab1ab98d1b33c2440646214d3356e20488d1a067f","observation_id":"d55ff7b2-43bf-402a-baf2-e50d9704b5d3","resolution":{"observed_at":"2026-08-11T14:13:50.239671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.224400Z","title":"What made this test flake? pinpointing classes responsible for test flakiness,","venue":null,"work_id":"fc072f29-04b3-47b8-b3c0-c1d5da328de3","year":2022},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.016790Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:c102331d91d40f0c67000ade0e2cb2c00171b35846728f06062db20fffadcf81","observation_id":"dc1fa1ec-9ff2-4c4e-baa9-a2d81d69454a","resolution":{"observed_at":"2026-08-11T14:13:50.228199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.213421Z","title":"ifixflakies: a framework for automatically fixing order-dependent flaky tests,","venue":null,"work_id":"9d3fa363-b7b9-4e8d-b79b-7f8169426526","year":2019},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.019672Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:89f748adec9b41e4a038287b072eb06b7644e1d46dbfc1595868e4fc9d88ea78","observation_id":"51942a95-27e3-4cff-b3de-ea5b5bf2e8c5","resolution":{"observed_at":"2026-08-11T14:13:50.217292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08406","last_updated":"2024-01-30T13:55:34Z","snapshot_observed_at":"2026-08-16T14:27:06.444067Z","submitted_at":"2024-01-16T14:44:47Z","title":"RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.08406","snapshot_observed_at":"2026-08-11T14:13:50.022795Z","title":"Rag vs fine -tuning: Pipelines, tradeoffs, and a case study on agriculture,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.022795Z"},"links":{"cited_paper":"/paper/2401.08406","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:a7d7ecc2990f1653239614d5c0b99867794143d811c4a9ff2afc75b187760d16","observation_id":"82032150-6fcd-4a65-96f3-ce1859ce36a1","resolution":{"observed_at":"2026-08-11T14:13:50.022795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-11T14:13:50.026542Z","title":"Llama 2: Open foundation and fine -tuned chat models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.026542Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:ef7dd41137499e61029d18ee529692e96ccf550aebb186ffe523ece2ae3d2269","observation_id":"141880eb-6bd0-4415-9ada-63eed7446f8f","resolution":{"observed_at":"2026-08-11T14:13:50.026542Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-11T14:13:50.030376Z","title":"Mistral 7b,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.030376Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:d9799987fa60cdc6578c802fa1a34469984057d68b55e0467653262ca49c72dc","observation_id":"1b770075-94dd-4863-b16e-33d27bf3099c","resolution":{"observed_at":"2026-08-11T14:13:50.030376Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-11T08:20:29.798517Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-11T14:13:50.033926Z","title":"Lora: Low - rank adaptation of large language models,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.033926Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:3ba47589d40d7d6b2c9e142b611a63ba21c7499b5b3a9ba6652af902686e994c","observation_id":"7db73e46-d085-48aa-aaf9-c403fe48853a","resolution":{"observed_at":"2026-08-11T14:13:50.033926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01208","last_updated":"2023-10-02T13:53:03Z","snapshot_observed_at":"2026-08-16T14:55:51.371919Z","submitted_at":"2023-10-02T13:53:03Z","title":"Label Supervised LLaMA Finetuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01208","snapshot_observed_at":"2026-08-11T14:13:50.037263Z","title":"Label supervised llama finetuning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.037263Z"},"links":{"cited_paper":"/paper/2310.01208","citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:94cac00ac933155b4f764be3962428ea18ded7917c7c2011553cd53f032d938f","observation_id":"458f200b-cead-479c-b64c-75d82ffc857e","resolution":{"observed_at":"2026-08-11T14:13:50.037263Z","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":"2026-08-11T14:13:50.201740Z","title":"Scikit-learn: Machine learning in Python,","venue":null,"work_id":"2fc7b063-2ff6-44d6-a78f-f3b2237d1923","year":2011},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.040984Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:01d1e5d2fb1ff9e9cbfff8d340d3849d25793cc3d605c7b7779df864b3af747a","observation_id":"7ebf1882-fbd2-4da6-be38-22016180abaf","resolution":{"observed_at":"2026-08-11T14:13:50.205537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.190701Z","title":"Evaluating large language models trained on code,","venue":null,"work_id":"45861617-95a1-4b38-872c-8afcbd8558dc","year":2021},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.044343Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:bc0c2eb1396c673d7127c2acef1697da8cc106843cbc7997af2d03e261b630f8","observation_id":"c40f4247-6c86-4f92-803b-8a251bd16bae","resolution":{"observed_at":"2026-08-11T14:13:50.194476Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T14:13:50.179247Z","title":"Fine tuning vs. retrieval augmented generation for less popular knowledge,","venue":null,"work_id":"a0870804-4812-4640-8355-263f2052022a","year":2024},"citing_paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T14:13:50.047565Z"},"links":{"citing_paper":"/paper/2412.12340"},"observation_digest":"sha256:e351f2bdb7670f94c581a20c7bfbbbbdc718a1247bd9677c3b79496100888df5","observation_id":"ef871e5c-aa09-4a2f-829b-94c9ff729b11","resolution":{"observed_at":"2026-08-11T14:13:50.184042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.12340","last_updated":"2025-06-05T20:45:15Z","latest_version":2,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-15T12:55:13.750951Z","submitted_at":"2024-12-16T20:20:45Z","title":"A Large Language Model Approach to Identify Flakiness in C++ Projects"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":32},"total_outbound_references":43},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.12340."}