{"as_of":"2026-08-09T18:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:187e2d0d4660055e3a686f59aa9ef0329e9bb83fa18e48ff7b3d546dea0881fa","coverage":[{"denominator":59,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":59,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:01:08.735443Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:54:59.035677Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T08:57:48.266442Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.09003","snapshot_observed_at":"2026-08-06T16:54:59.035677Z","title":"Swe-flow: Synthesizing software engineering data in a test-driven manner","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.12415","last_updated":"2026-07-01T03:29:05Z","snapshot_observed_at":"2026-08-06T16:43:57.286862Z","submitted_at":"2025-07-16T17:05:17Z","title":"SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories?","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T16:54:59.035677Z"},"links":{"cited_paper":"/paper/2506.09003","citing_paper":"/paper/2507.12415"},"observation_digest":"sha256:0b3432376b2094896da4af96b5721ea6730f2e522f4133b20cc49c002e8ac028","observation_id":"eb6a543c-bd24-466d-b4fd-af2563c2b9dd","resolution":{"observed_at":"2026-08-06T16:54:59.035677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"cited_work":{"arxiv_id":"2506.09003","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09003","snapshot_observed_at":"2026-07-03T08:57:48.266442Z","title":"arXiv preprint arXiv:2506.09003 , year=","venue":null,"work_id":"83d75eca-c07b-46b1-bc71-8ef34842eb24","year":null},"citing_paper":{"arxiv_id":"2605.15226","last_updated":"2026-05-13T14:14:54Z","snapshot_observed_at":"2026-07-06T23:26:32.979566Z","submitted_at":"2026-05-13T14:14:54Z","title":"Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-19T17:49:01.198956Z"},"links":{"cited_paper":"/paper/2506.09003","citing_paper":"/paper/2605.15226"},"observation_digest":"sha256:fa203f260bd6188620141c80caabf91586cb32d67fdfe15d1f06368139543409","observation_id":"9e6bcce1-20c6-48a1-8e19-34d221c68d52","resolution":{"observed_at":"2026-05-19T17:52:42.992829Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"cited_work":{"arxiv_id":"2506.09003","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.09003","snapshot_observed_at":"2026-07-03T08:57:48.266442Z","title":"arXiv preprint arXiv:2506.09003 , year=","venue":null,"work_id":"83d75eca-c07b-46b1-bc71-8ef34842eb24","year":null},"citing_paper":{"arxiv_id":"2606.18284","last_updated":"2026-06-10T02:04:29Z","snapshot_observed_at":"2026-07-06T23:53:45.117607Z","submitted_at":"2026-06-10T02:04:29Z","title":"Breaking the Solver Bottleneck: Training Task Generators at the Learnable Frontier","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-06-27T10:36:09.211639Z"},"links":{"cited_paper":"/paper/2506.09003","citing_paper":"/paper/2606.18284"},"observation_digest":"sha256:cdd85fba048e6a1b35f799ccd68496678ae2beca66feb19e0d5f7bf0687a0661","observation_id":"4f8f2d29-e9cb-42ee-82ad-a5a7250532cd","resolution":{"observed_at":"2026-07-03T08:57:48.267846Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.09003/citation-record","integrity":"/paper/2506.09003/integrity","json":"/paper/2506.09003/citation-record.json","paper":"/paper/2506.09003"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:01:10.476142Z","title":"Claude 3 family, 2024","venue":null,"work_id":"936c5c99-1877-434b-a4a2-7647b9591531","year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.474210Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:cf94290e7c5b2d46b39932e156e55798d3f20b4244c8df86ef9ffda126b84958","observation_id":"396625a1-f3b0-48c5-b91b-515431943a4b","resolution":{"observed_at":"2026-08-07T05:01:10.551858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07732","last_updated":"2021-08-16T03:57:30Z","snapshot_observed_at":"2026-08-02T19:23:53.535075Z","submitted_at":"2021-08-16T03:57:30Z","title":"Program Synthesis with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07732","snapshot_observed_at":"2026-08-07T05:01:08.479429Z","title":"Program synthesis with large language models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.479429Z"},"links":{"cited_paper":"/paper/2108.07732","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:25c8bc9dc3bd0bb3d6c5eb1a49103fcca714b8eb61c58ab83dcb45bc4e4bf5e3","observation_id":"148497a2-5abc-4c24-92c4-8286d3122ab5","resolution":{"observed_at":"2026-08-07T05:01:08.479429Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.14255","last_updated":"2022-07-28T17:40:47Z","snapshot_observed_at":"2026-08-07T11:38:07.397956Z","submitted_at":"2022-07-28T17:40:47Z","title":"Efficient Training of Language Models to Fill in the Middle","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.14255","snapshot_observed_at":"2026-08-07T05:01:08.484322Z","title":"Efficient training of language models to fill in the middle","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.484322Z"},"links":{"cited_paper":"/paper/2207.14255","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:0ab6f01a9392c898922906a8b77fc8ecd054649f1d2e63b46183cd41150c2689","observation_id":"4985abcb-a917-4a1c-a0b4-373f3045aaa7","resolution":{"observed_at":"2026-08-07T05:01:08.484322Z","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":"2026-08-07T05:01:10.408151Z","title":"Test Driven Development: By Example","venue":null,"work_id":"9efeac1b-9a44-4924-99d0-ef33a6e22066","year":2002},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.488707Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:6224638c2e1bbd59cc79c8d820c1c24975ccb2b7b182059ef9b0dd5a4fce522c","observation_id":"e73688e8-216e-4e97-9129-08ffc7b77aaf","resolution":{"observed_at":"2026-08-07T05:01:10.442714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T05:01:08.492348Z","title":"J., Feldman, M","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.492348Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:ff75224dad51d6471b7ce6c586d72f98ef9eb457876c34682c0fa2adc7994c01","observation_id":"f1cb6808-04da-4691-a4e4-a08150bf311f","resolution":{"observed_at":"2026-08-07T05:01:08.492348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07436","last_updated":"2024-06-11T16:45:17Z","snapshot_observed_at":"2026-07-06T18:29:00.001236Z","submitted_at":"2024-06-11T16:45:17Z","title":"McEval: Massively Multilingual Code Evaluation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07436","snapshot_observed_at":"2026-08-07T05:01:08.496370Z","title":"Mceval: Massively multilingual code evaluation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.496370Z"},"links":{"cited_paper":"/paper/2406.07436","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:97cb93033ad61449acd2bdb189265b69accef342173f0594160012f5fdbaf3cb","observation_id":"34c28701-ec53-491d-ac55-6e1835c1cc3f","resolution":{"observed_at":"2026-08-07T05:01:08.496370Z","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":"2026-08-07T05:01:10.244943Z","title":"Code alpaca: An instruction-following llama model for code generation","venue":null,"work_id":"eee9ed32-df30-4e4a-83fc-aa5edaf95bc9","year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.500665Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:a6f5c1d718b0447fcd488b4d04530609581aca0c3fb9b767ada72563d9b51065","observation_id":"422008cd-f3dd-404d-9bfc-47423db6a024","resolution":{"observed_at":"2026-08-07T05:01:10.300217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-08-08T11:58:24.516369Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-07T05:01:08.504089Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.504089Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:4d66143805a5e7cc854340b66e70b89000be2808fbac2c6000fb0e234656f94f","observation_id":"fe99a3f4-421e-4bdd-b8ea-849e856352d8","resolution":{"observed_at":"2026-08-07T05:01:08.504089Z","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":"2026-08-07T05:01:10.139536Z","title":"Fullstack bench: Evaluating llms as full stack coders","venue":null,"work_id":"2ae70216-9770-446a-be7b-fb01ae1b5359","year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.507692Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:ad4c8721fde29cafe3a048974c5da8b0d652bded3f9546543c363889e201aedf","observation_id":"5e442615-3f4d-4025-9f9e-4dec4518f998","resolution":{"observed_at":"2026-08-07T05:01:10.202212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T05:01:09.995315Z","title":null,"venue":null,"work_id":"de318bb8-62c0-4d57-b09f-b742e7056959","year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.512169Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:5920804060df20bb8cdd5befd29e71b5ccd3fbcd31831e9761e28135af2212f8","observation_id":"8ed31676-e688-4629-bc5b-e5c964992966","resolution":{"observed_at":"2026-08-07T05:01:10.039972Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14196","last_updated":"2024-01-26T09:23:11Z","snapshot_observed_at":"2026-08-06T22:40:28.707813Z","submitted_at":"2024-01-25T14:17:53Z","title":"DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.14196","snapshot_observed_at":"2026-08-07T05:01:08.515327Z","title":"Deepseek-coder: When the large language model meets programming--the rise of code intelligence","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.515327Z"},"links":{"cited_paper":"/paper/2401.14196","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:70b21cbefd2a44310e1b325443bb71dc848155bcd53d1d3670d119f62e2fd161","observation_id":"469fccc6-d802-4ed2-a002-d35451dd7353","resolution":{"observed_at":"2026-08-07T05:01:08.515327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-07T05:01:08.519401Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.519401Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:dad112eeed3392afc217706731e0996d05c39e74d5051a0c8e5ee5bd7d297c8c","observation_id":"cb5149ce-d329-4e28-aa70-41d3d98f6fd0","resolution":{"observed_at":"2026-08-07T05:01:08.519401Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00352","last_updated":"2024-11-01T14:36:52Z","snapshot_observed_at":"2026-07-06T16:01:07.532053Z","submitted_at":"2023-08-01T07:49:10Z","title":"MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00352","snapshot_observed_at":"2026-08-07T05:01:08.522960Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.522960Z"},"links":{"cited_paper":"/paper/2308.00352","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:157eaca04bdb0df09fe1fc61425229c5977d3831d22f9b9b63d8260d432e2180","observation_id":"c2bb375d-f21f-409f-bbd2-e0b14872c100","resolution":{"observed_at":"2026-08-07T05:01:08.522960Z","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":"2026-08-07T05:01:09.837838Z","title":"Cosqa: 20,000+ web queries for code search and question answering","venue":null,"work_id":"2af62023-3892-4952-9ffe-635b4d3aa19c","year":2021},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.527327Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:583517ab11333315325a1f921e187db860e9e42d3dc3ac5901a513129fafca6e","observation_id":"914b9a65-a169-4853-a396-d30beccec76f","resolution":{"observed_at":"2026-08-07T05:01:09.921589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04905","last_updated":"2025-03-20T03:28:56Z","snapshot_observed_at":"2026-08-08T14:21:42.036023Z","submitted_at":"2024-11-07T17:47:25Z","title":"OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04905","snapshot_observed_at":"2026-08-07T05:01:08.531079Z","title":"K., Hao, J., Song, L., Xu, Y., Yang, J., Liu, J., Zhang, C., Chai, L., et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.531079Z"},"links":{"cited_paper":"/paper/2411.04905","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:db711c935a91f7c338d9104d24b7f97c24d987069460ada7cc54f00f606559e1","observation_id":"604ccd9b-19ad-42d2-88da-1e6e881894a8","resolution":{"observed_at":"2026-08-07T05:01:08.531079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12186","last_updated":"2024-11-12T13:24:25Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-18T17:57:57Z","title":"Qwen2.5-Coder Technical Report","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12186","snapshot_observed_at":"2026-08-07T05:01:08.534856Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.534856Z"},"links":{"cited_paper":"/paper/2409.12186","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:5f336dc82d5169be285d14a4fade14bc3df855e6119bb3cf8acc4355c5a04cf9","observation_id":"a0fbaa5b-66f1-41b0-8eaa-7dce963b43d5","resolution":{"observed_at":"2026-08-07T05:01:08.534856Z","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":"2026-08-07T05:01:09.764188Z","title":null,"venue":null,"work_id":"6c8078cb-2ef4-4870-981c-d981065c23f2","year":2022},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.538959Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:a310490b8344a827b5d325391ecf202e03a63cfb6b0843ae9c0c010468e73193","observation_id":"cb8600d7-aa7d-426b-a0e3-95c8743b81c1","resolution":{"observed_at":"2026-08-07T05:01:09.795207Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-07T05:01:08.543138Z","title":"P., Perelman, A., Ramesh, A., Clark, A., Ostrow, A., Welihinda, A., Hayes, A., Radford, A., et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.543138Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:28fe8577c01a7437789f40f59c1d3d32ea34952b96c288640dac5e9f8d772fc2","observation_id":"d71fdfd5-32fe-441c-93ea-c5aa533c1081","resolution":{"observed_at":"2026-08-07T05:01:08.543138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.09436","last_updated":"2020-06-08T09:09:28Z","snapshot_observed_at":"2026-08-06T10:54:14.530969Z","submitted_at":"2019-09-20T11:52:45Z","title":"CodeSearchNet Challenge: Evaluating the State of Semantic Code Search","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.09436","snapshot_observed_at":"2026-08-07T05:01:08.548148Z","title":"Codesearchnet challenge: Evaluating the state of semantic code search","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.548148Z"},"links":{"cited_paper":"/paper/1909.09436","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:f6db5bd005841ed3eb5b80b9465958ad261705a291c5ed9c9a5a70f232d7f9b5","observation_id":"c12fddc4-2bc5-43e5-8bee-84548098ab65","resolution":{"observed_at":"2026-08-07T05:01:08.548148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-08-07T05:01:08.553169Z","title":"Openai o1 system card","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.553169Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:7da91339a8b493ad4c627001ba8a28579b1d465b41c24e822e34009101d21ca1","observation_id":"d6ebfacc-bffc-43b1-8d7a-2b83551e1920","resolution":{"observed_at":"2026-08-07T05:01:08.553169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07974","last_updated":"2024-06-06T17:41:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-03-12T17:58:04Z","title":"LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.07974","snapshot_observed_at":"2026-08-07T05:01:08.557070Z","title":"Livecodebench: Holistic and contamination free evaluation of large language models for code","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.557070Z"},"links":{"cited_paper":"/paper/2403.07974","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:5edef7d742db8250983fe3335e4e0b8d0d006b3b5a68ccc3650d7b4cbcd5bf92","observation_id":"a3209cb2-f9d5-4da4-b330-5c1d4a935022","resolution":{"observed_at":"2026-08-07T05:01:08.557070Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06770","last_updated":"2024-11-11T23:05:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-10T16:47:29Z","title":"SWE-bench: Can Language Models Resolve Real-World GitHub Issues?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06770","snapshot_observed_at":"2026-08-07T05:01:08.560875Z","title":"E., Yang, J., Wettig, A., Yao, S., Pei, K., Press, O., and Narasimhan, K","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.560875Z"},"links":{"cited_paper":"/paper/2310.06770","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:dfadb04fbc83df5953fc026a84c669f727ffd2fb74f6110d5a189846f8c59863","observation_id":"0c09a16e-0c3f-4bf9-a70e-a52ad40f3a53","resolution":{"observed_at":"2026-08-07T05:01:08.560875Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.11501","last_updated":"2022-11-18T17:20:27Z","snapshot_observed_at":"2026-08-09T13:53:26.987097Z","submitted_at":"2022-11-18T17:20:27Z","title":"DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.11501","snapshot_observed_at":"2026-08-07T05:01:08.565717Z","title":"Ds-1000: A natural and reliable benchmark for data science code generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.565717Z"},"links":{"cited_paper":"/paper/2211.11501","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:d3350149c97ef75b3f8e6a08a28b272a19d4d33f7a0ecff24bfdca3e4283f883","observation_id":"d7348bda-a1b0-46a0-ae12-4c3055b0e81a","resolution":{"observed_at":"2026-08-07T05:01:08.565717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06161","last_updated":"2023-12-13T14:44:10Z","snapshot_observed_at":"2026-07-06T15:25:35.930688Z","submitted_at":"2023-05-09T08:16:42Z","title":"StarCoder: may the source be with you!","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06161","snapshot_observed_at":"2026-08-07T05:01:08.570403Z","title":"B., Zi, Y., Muennighoff, N., Kocetkov, D., Mou, C., Marone, M., Akiki, C., Li, J., Chim, J., Liu, Q., Zheltonozhskii, E., Zhuo, T","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.570403Z"},"links":{"cited_paper":"/paper/2305.06161","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:e0d294d0ea6c509edd2c905b4e27dd3cfc7d42f1f56a405a0bf3128c87cef993","observation_id":"dda165a8-2002-45fd-9aa7-b572a9c97e87","resolution":{"observed_at":"2026-08-07T05:01:08.570403Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.20424","last_updated":"2024-11-05T19:46:38Z","snapshot_observed_at":"2026-08-09T09:48:01.790453Z","submitted_at":"2024-10-27T12:44:25Z","title":"AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.20424","snapshot_observed_at":"2026-08-07T05:01:08.574502Z","title":"Autokaggle: A multi-agent framework for autonomous data science competitions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.574502Z"},"links":{"cited_paper":"/paper/2410.20424","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:f1f9a589b7241c4f114b8f49299cd46537585223cced112a3bf3f9790d5aa761","observation_id":"8e9ec177-bc41-4190-965b-3f7ff071d622","resolution":{"observed_at":"2026-08-07T05:01:08.574502Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19437","last_updated":"2025-02-18T17:26:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-27T04:03:16Z","title":"DeepSeek-V3 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19437","snapshot_observed_at":"2026-08-07T05:01:08.579099Z","title":"Deepseek-v3 technical report","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.579099Z"},"links":{"cited_paper":"/paper/2412.19437","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:8cc613dc33715140f3f752c889a4c7864649f1a9348b836a5361e25188f70028","observation_id":"5362c7ad-8228-4eeb-84af-ea06d5f878fa","resolution":{"observed_at":"2026-08-07T05:01:08.579099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.01210","last_updated":"2023-10-30T19:37:09Z","snapshot_observed_at":"2026-08-09T13:00:51.978208Z","submitted_at":"2023-05-02T05:46:48Z","title":"Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.01210","snapshot_observed_at":"2026-08-07T05:01:08.583838Z","title":"S., Wang, Y., and Zhang, L","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.583838Z"},"links":{"cited_paper":"/paper/2305.01210","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:89a4ccc8669c95c6b12682220a6e812b03ab04bf595df19ee014ca641d4a101e","observation_id":"f91b6487-e940-4a96-915a-0d6f1ab6685d","resolution":{"observed_at":"2026-08-07T05:01:08.583838Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21157","last_updated":"2024-10-28T15:58:41Z","snapshot_observed_at":"2026-08-09T09:47:42.620690Z","submitted_at":"2024-10-28T15:58:41Z","title":"M2rc-Eval: Massively Multilingual Repository-level Code Completion Evaluation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21157","snapshot_observed_at":"2026-08-07T05:01:08.588208Z","title":"M2rc-eval: Massively multilingual repository-level code completion evaluation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.588208Z"},"links":{"cited_paper":"/paper/2410.21157","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:6210b7a0e9a28e29b5aaad6cd709021ebea2314a31bcced0d693bf0592700142","observation_id":"47934f7e-c1cd-42be-b749-fceb4817747d","resolution":{"observed_at":"2026-08-07T05:01:08.588208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.02310","last_updated":"2025-02-24T09:25:51Z","snapshot_observed_at":"2026-08-04T04:41:35.684065Z","submitted_at":"2024-11-04T17:36:40Z","title":"MdEval: Massively Multilingual Code Debugging","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.02310","snapshot_observed_at":"2026-08-07T05:01:08.596608Z","title":"Mdeval: Massively multilingual code debugging","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.596608Z"},"links":{"cited_paper":"/paper/2411.02310","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:b2625f86b8647f8db405ab96e5d7bdcaf9e077977c75cd89452a65633b9e0829","observation_id":"e820ebc9-02f7-4f03-9e2e-341cfad81572","resolution":{"observed_at":"2026-08-07T05:01:08.596608Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.19173","last_updated":"2024-02-29T13:53:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-29T13:53:35Z","title":"StarCoder 2 and The Stack v2: The Next Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.19173","snapshot_observed_at":"2026-08-07T05:01:08.600565Z","title":"B., Cassano, F., Lamy-Poirier, J., Tazi, N., Tang, A., Pykhtar, D., Liu, J., Wei, Y., et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.600565Z"},"links":{"cited_paper":"/paper/2402.19173","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:b9408a2836a857d5b28d9e83b2121d8e3509da4f9cf1469dd37eead887bc41f6","observation_id":"98f65e04-4ae3-49c3-be04-df13f0e485d8","resolution":{"observed_at":"2026-08-07T05:01:08.600565Z","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":"2026-08-07T05:01:09.677339Z","title":"K., Fu, S., and LIU, S","venue":null,"work_id":"40dcbfd5-2303-4152-9f97-9801038adfaa","year":2021},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.604486Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:42e81a84095868654b68618e681d3b3635642e3d81e0c5378052e86774e51ad0","observation_id":"4c12e9db-3e82-4596-930b-cbf459d54d98","resolution":{"observed_at":"2026-08-07T05:01:09.693244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.08568","last_updated":"2025-05-27T07:40:36Z","snapshot_observed_at":"2026-08-04T15:08:40.203853Z","submitted_at":"2023-06-14T15:18:48Z","title":"WizardCoder: Empowering Code Large Language Models with Evol-Instruct","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.08568","snapshot_observed_at":"2026-08-07T05:01:08.608475Z","title":"Wizardcoder: Empowering code large language models with evol-instruct","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.608475Z"},"links":{"cited_paper":"/paper/2306.08568","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:abe5559af8918d800573b1d6a95e17e780805050b654c3f73e39d7a23231f28f","observation_id":"9c917e05-0e44-4d2a-b72d-a182766905a0","resolution":{"observed_at":"2026-08-07T05:01:08.608475Z","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":"2026-08-07T05:01:09.649018Z","title":"Training language models to follow instructions with human feedback","venue":null,"work_id":"2ce7d4b7-736b-4c60-a063-d4a26f4e231b","year":2022},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.613596Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:f61c95ff686a0efd4d6ed38930fd9f4bd5e9076cf426ba8db427560ef252cbdc","observation_id":"c9ba37a4-a554-498f-a5ac-7b4747fec391","resolution":{"observed_at":"2026-08-07T05:01:09.659091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T05:01:09.611151Z","title":"L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Kelton, F., Miller, L., Simens, M., Askell, A., Welinder, P., Christiano, P","venue":null,"work_id":"aec37ebd-c5a4-4173-b018-d63e86c69c72","year":2022},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.617756Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:820fd8f71a5ac7cc2fc909b6cfb6172978619040502517ee55d4be46bbb8d04c","observation_id":"0ca40508-c6f8-4201-b992-0701c9f244cf","resolution":{"observed_at":"2026-08-07T05:01:09.627162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.21139","last_updated":"2025-06-06T07:53:20Z","snapshot_observed_at":"2026-07-06T20:14:49.976782Z","submitted_at":"2024-12-30T18:15:39Z","title":"Training Software Engineering Agents and Verifiers with SWE-Gym","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.21139","snapshot_observed_at":"2026-08-07T05:01:08.621436Z","title":"Training software engineering agents and verifiers with swe-gym","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.621436Z"},"links":{"cited_paper":"/paper/2412.21139","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:01d102685e97db59c6c7318b411117e8d89810159165e69cb866edcd8660dc85","observation_id":"7b6650e9-34c6-452e-848c-6b2b2fdb50fd","resolution":{"observed_at":"2026-08-07T05:01:08.621436Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.12950","last_updated":"2024-01-31T19:47:26Z","snapshot_observed_at":"2026-07-06T16:10:07.931347Z","submitted_at":"2023-08-24T17:39:13Z","title":"Code Llama: Open Foundation Models for Code","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.12950","snapshot_observed_at":"2026-08-07T05:01:08.625719Z","title":"E., Adi, Y., Liu, J., Remez, T., Rapin, J., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.625719Z"},"links":{"cited_paper":"/paper/2308.12950","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:0c867a24e8b3d0b2b6235d872544dc4191a6a58a003492b0e57074724b7df55b","observation_id":"75d28364-3e0a-44c2-995d-e97a0f75fa7a","resolution":{"observed_at":"2026-08-07T05:01:08.625719Z","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":"2026-08-07T05:01:09.578918Z","title":"Toolformer: Language models can teach themselves to use tools","venue":null,"work_id":"7758c371-342b-499e-8878-5c47c533b855","year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.629824Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:05d307cb118b58f322c58e92954e985f6309a4b174cfebff12de99b9e51c368d","observation_id":"7d6b3e52-5b3a-48ea-b89f-5e039b97a1f4","resolution":{"observed_at":"2026-08-07T05:01:09.592384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.08053","last_updated":"2020-03-13T23:45:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-09-17T19:42:54Z","title":"Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.08053","snapshot_observed_at":"2026-08-07T05:01:08.633430Z","title":"Megatron-lm: Training multi-billion parameter language models using model parallelism","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.633430Z"},"links":{"cited_paper":"/paper/1909.08053","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:d15987d4b6ee00330faa8a9873411521af2c684e9cc07fbf9dc7cb5be59594d6","observation_id":"5c273352-3931-4d6b-a04f-e62ca35e70f5","resolution":{"observed_at":"2026-08-07T05:01:08.633430Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.02059","last_updated":"2024-11-07T03:32:44Z","snapshot_observed_at":"2026-08-07T15:32:17.369903Z","submitted_at":"2024-11-04T13:03:13Z","title":"TableGPT2: A Large Multimodal Model with Tabular Data Integration","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.02059","snapshot_observed_at":"2026-08-07T05:01:08.638594Z","title":"Tablegpt2: A large multimodal model with tabular data integration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.638594Z"},"links":{"cited_paper":"/paper/2411.02059","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:71f2520b926526130ed1e1c4435e3ebdf46e3c359c106a2bf7b6bdcd543347bc","observation_id":"794b2ab7-43e2-47bb-80f0-83534dfd3a17","resolution":{"observed_at":"2026-08-07T05:01:08.638594Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03314","last_updated":"2023-06-05T23:55:37Z","snapshot_observed_at":"2026-08-05T20:35:55.884484Z","submitted_at":"2023-06-05T23:55:37Z","title":"Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03314","snapshot_observed_at":"2026-08-07T05:01:08.642941Z","title":"and Nadiri, A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.642941Z"},"links":{"cited_paper":"/paper/2306.03314","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:48f08d5dee353f34178c335774d26bc4222001ab2397a2de65324d058a117a1e","observation_id":"e8e6fe4b-d594-4d1c-8b7f-71d291424192","resolution":{"observed_at":"2026-08-07T05:01:08.642941Z","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":"2026-08-07T05:01:09.540037Z","title":"Debugbench: Evaluating debugging capability of large language models","venue":null,"work_id":"49b7a281-238a-488f-a366-dc67be12502a","year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.647532Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:2b32b34caf1d5d41c4b356df58bfc1da3eeccb9144e6797a7aa1724642669a14","observation_id":"3af6f564-9d0d-4f72-809b-94b0ff7f0bd3","resolution":{"observed_at":"2026-08-07T05:01:09.557352Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T05:01:08.657036Z","title":"F., Tang, X., Zhuge, M., Pan, J., Song, Y., Li, B., Singh, J., et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.657036Z"},"links":{"cited_paper":"/paper/2407.16741","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:e0a707bfa080e5e0fced6682221377bd3cee6b5c104fa4adb1d3e0adbed34b2b","observation_id":"3a8c69dc-d40b-43a2-af06-0dea281564c2","resolution":{"observed_at":"2026-08-07T05:01:08.657036Z","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":"2026-08-07T05:01:08.660669Z","title":"A., Khashabi, D., and Hajishirzi, H","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.660669Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:3fa4482e793cfc8594637bd22696df86d47dcb021412a388ed8aa633127e185c","observation_id":"27834aad-e56d-42c7-a195-ed415f2661c4","resolution":{"observed_at":"2026-08-07T05:01:08.660669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.02120","last_updated":"2024-06-07T02:50:56Z","snapshot_observed_at":"2026-07-06T16:56:46.051958Z","submitted_at":"2023-12-04T18:50:35Z","title":"Magicoder: Empowering Code Generation with OSS-Instruct","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.02120","snapshot_observed_at":"2026-08-07T05:01:08.664935Z","title":"Magicoder: Source code is all you need","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.664935Z"},"links":{"cited_paper":"/paper/2312.02120","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:f3af6e14d205cdb8a87779e502f50304ed81150b105f7afe7d0916b47d59c62c","observation_id":"a5549e19-d759-4218-8369-73cc2989c550","resolution":{"observed_at":"2026-08-07T05:01:08.664935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.09174","last_updated":"2025-03-18T07:13:18Z","snapshot_observed_at":"2026-08-09T09:48:05.918224Z","submitted_at":"2024-08-17T11:40:10Z","title":"TableBench: A Comprehensive and Complex Benchmark for Table Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.09174","snapshot_observed_at":"2026-08-07T05:01:08.669060Z","title":"Tablebench: A comprehensive and complex benchmark for table question answering","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.669060Z"},"links":{"cited_paper":"/paper/2408.09174","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:88538ca68405ee6b0c202ae7d1625600350286f46a624105941225a34f524b38","observation_id":"f74edbeb-1443-4575-af5b-1076920d69ad","resolution":{"observed_at":"2026-08-07T05:01:08.669060Z","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":"2026-08-07T05:01:09.513087Z","title":"Codetransocean: A comprehensive multilingual benchmark for code translation","venue":null,"work_id":"c368d20c-6c9c-4a5a-b55c-4e8a0ef6593c","year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.673784Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:78e3eac863d0ae8b614aac86d6e6f2ba220c3a2a62208d89264589ad2814837a","observation_id":"0d1ae447-a3f6-4851-a7ff-e8cd65b88d32","resolution":{"observed_at":"2026-08-07T05:01:09.525726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-07T05:01:08.678098Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.678098Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:7b56f840d39f9c267b3222b819b5cd232acc159762ec357c3db707adba08b094","observation_id":"b7be68dc-f378-4dcd-9d5f-394b4a9ed41c","resolution":{"observed_at":"2026-08-07T05:01:08.678098Z","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":"2026-08-07T05:01:08.686435Z","title":"E., Wettig, A., Lieret, K., Yao, S., Narasimhan, K., and Press, O","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.686435Z"},"links":{"cited_paper":"/paper/2405.15793","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:34950707dc1db16d9ca62674f34d240ca8fce1085dfc4ecfefa81f91e42dbe87","observation_id":"2a55b4e8-1df3-486d-87aa-763c2bf346c5","resolution":{"observed_at":"2026-08-07T05:01:08.686435Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05210","last_updated":"2024-12-06T17:40:38Z","snapshot_observed_at":"2026-07-06T20:02:57.733746Z","submitted_at":"2024-12-06T17:40:38Z","title":"Evaluating and Aligning CodeLLMs on Human Preference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05210","snapshot_observed_at":"2026-08-07T05:01:08.691383Z","title":"Evaluating and aligning codellms on human preference","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.691383Z"},"links":{"cited_paper":"/paper/2412.05210","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:ea8da51944f5cbc4fcc3db19ee2432bfcbb86a3f3981b8df0e8db59d45f01425","observation_id":"073c3344-a1c6-4959-97b2-6664f89ac870","resolution":{"observed_at":"2026-08-07T05:01:08.691383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.11990","last_updated":"2024-12-16T17:14:35Z","snapshot_observed_at":"2026-08-04T05:43:25.698966Z","submitted_at":"2024-12-16T17:14:35Z","title":"ExecRepoBench: Multi-level Executable Code Completion Evaluation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.11990","snapshot_observed_at":"2026-08-07T05:01:08.695802Z","title":"Execrepobench: Multi-level executable code completion evaluation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.695802Z"},"links":{"cited_paper":"/paper/2412.11990","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:bfa7e7021bf94617d30fa7880a43f8f0b953ace4a08409f9608298457708a8d3","observation_id":"267cdb0a-3c8e-4631-ba20-2523a31c0a6d","resolution":{"observed_at":"2026-08-07T05:01:08.695802Z","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":"2026-08-07T05:01:09.479216Z","title":"Codereval: A benchmark of pragmatic code generation with generative pre-trained models","venue":null,"work_id":"3f5871ae-d14c-44ac-858f-48551ce7953b","year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.700051Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:f4c181c072b1833ef61660c57fef78354b408e4a2006bbef4253ae88905de572","observation_id":"6e60197e-b0f4-4a01-93aa-207df3377510","resolution":{"observed_at":"2026-08-07T05:01:09.492710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.14187","last_updated":"2024-06-07T07:46:28Z","snapshot_observed_at":"2026-07-06T17:06:45.522731Z","submitted_at":"2023-12-20T09:02:29Z","title":"WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.14187","snapshot_observed_at":"2026-08-07T05:01:08.704352Z","title":"Wavecoder: Widespread and versatile enhanced instruction tuning with refined data generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.704352Z"},"links":{"cited_paper":"/paper/2312.14187","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:175378ed6020a477331cca072d61dfb4efe1b93950b7a1a9df7bd0839e7952ba","observation_id":"7e5aa239-4bdd-461f-976c-ee8b1f02ecd7","resolution":{"observed_at":"2026-08-07T05:01:08.704352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.12570","last_updated":"2023-10-20T15:21:51Z","snapshot_observed_at":"2026-07-06T15:06:41.938212Z","submitted_at":"2023-03-22T13:54:46Z","title":"RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.12570","snapshot_observed_at":"2026-08-07T05:01:08.709819Z","title":"RepoCoder : Repository-level code completion through iterative retrieval and generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.709819Z"},"links":{"cited_paper":"/paper/2303.12570","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:820a0be1b54f9329ecbcfc813980f6adcbb9ab059f07795a01f4c3b2542f0f52","observation_id":"295dbe90-c05c-4855-aa7c-1ee4b44d0b57","resolution":{"observed_at":"2026-08-07T05:01:08.709819Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.13699","last_updated":"2025-01-23T14:27:11Z","snapshot_observed_at":"2026-08-09T04:34:25.738477Z","submitted_at":"2025-01-23T14:27:11Z","title":"DI-BENCH: Benchmarking Large Language Models on Dependency Inference with Testable Repositories at Scale","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.13699","snapshot_observed_at":"2026-08-07T05:01:08.713965Z","title":"Di-bench: Benchmarking large language models on dependency inference with testable repositories at scale","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.713965Z"},"links":{"cited_paper":"/paper/2501.13699","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:a70ab0a18ad68820ded7b76d2ae33239944ad2895b8867a59a90386c82a8f8b5","observation_id":"62009d9d-bf2f-45f4-bc76-859803f2ea11","resolution":{"observed_at":"2026-08-07T05:01:08.713965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.16199","last_updated":"2024-09-18T23:54:36Z","snapshot_observed_at":"2026-08-06T06:36:02.994951Z","submitted_at":"2023-03-28T17:59:12Z","title":"LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.16199","snapshot_observed_at":"2026-08-07T05:01:08.717994Z","title":"Llama-adapter: Efficient fine-tuning of language models with zero-init attention","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.717994Z"},"links":{"cited_paper":"/paper/2303.16199","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:ca329f736d30e56d81068ef55a2c632c1f23885dccc9c9ed9baab4d57263c796","observation_id":"7c785dcf-a180-4fae-9823-0fcd29b61a77","resolution":{"observed_at":"2026-08-07T05:01:08.717994Z","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":"2026-08-07T05:01:09.438011Z","title":"Naturalcodebench: Examining coding performance mismatch on humaneval and natural user queries","venue":null,"work_id":"96f38809-7334-4515-8372-462519693276","year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.722442Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:c096fd25191fc602f7cb34cc249713c092d7574629f99205c72fb0ba5861c1da","observation_id":"a3620268-48cc-49e8-ac2e-de0841a3d882","resolution":{"observed_at":"2026-08-07T05:01:09.456650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.01769","last_updated":"2024-12-02T18:11:30Z","snapshot_observed_at":"2026-08-04T23:09:46.525183Z","submitted_at":"2024-12-02T18:11:30Z","title":"Commit0: Library Generation from Scratch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.01769","snapshot_observed_at":"2026-08-07T05:01:08.726888Z","title":"T., Cardie, C., Gall \\'e , M., and Rush, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.726888Z"},"links":{"cited_paper":"/paper/2412.01769","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:8839b63818d930d1d5259e58df2e4f48f6a5b656f83ec3560c4d3157aca094ee","observation_id":"fbd5cac8-37fa-4c5d-895b-3dd6d16e92ac","resolution":{"observed_at":"2026-08-07T05:01:08.726888Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.15877","last_updated":"2025-04-01T08:36:44Z","snapshot_observed_at":"2026-07-31T19:00:59.311189Z","submitted_at":"2024-06-22T15:52:04Z","title":"BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.15877","snapshot_observed_at":"2026-08-07T05:01:08.731421Z","title":"Y., Vu, M","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.731421Z"},"links":{"cited_paper":"/paper/2406.15877","citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:6c2eeabd4e5bd183444c61de368c0f0334c012ce72e9f522331b061e16757d50","observation_id":"29638c0b-6a15-4651-b457-5c314976fef7","resolution":{"observed_at":"2026-08-07T05:01:08.731421Z","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":"2026-08-07T05:01:08.735443Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner","version":2},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-07T05:01:08.735443Z"},"links":{"citing_paper":"/paper/2506.09003"},"observation_digest":"sha256:9f7bde4b02fc79181a508504b49cc43fdfd8e7fe4be2bf1bd5ec5c27a334a273","observation_id":"1abd8736-f7dd-41b1-b3cb-ce42cf54afb0","resolution":{"observed_at":"2026-08-07T05:01:08.735443Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T09:48:08.035561Z","submitted_at":"2025-06-10T17:23:33Z","title":"SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner"},"reference_resolution":{"displayed":59,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":46,"verified_exact":0,"verified_fuzzy":13},"total_outbound_references":59},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 3 inbound Pith citation observations for arXiv:2506.09003."}