{"as_of":"2026-08-07T18:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3dfed6f4a22e72663c91abcbf3ae50b7cb646237f1e14a009c2aa7a555489001","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":"2026-08-07T06:34:17.273281+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":"2026-08-07T09:58:17.586754Z","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":"sha256:616855741155f5456068b7ef061d701d30ae1b3477d373f8e2dd48a2eee6bcb8","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":"2026-08-07T09:58:17.586754Z","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:f213580092dc9e0028cd65177d6b8e1ef35db56ec2716796d9f19c4dd145ecca","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.09003","last_updated":"2025-06-11T03:30:10Z","snapshot_observed_at":"2026-08-07T09:58:17.586754Z","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":"sha256:97387be224210c86d4f8d4f7ddbb13a118f0cc756b94dfcb0be2b4f302273bb3","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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:fc5b2fac62275ed87b712b92104bfe0d9f9cc9574bdbcbed0754f462d17d8497","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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":"sha256:14c80dd33aa85caaef58296092647e9ce0db14d0743f69a15041ff82b0f9547d","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":"2026-08-07T09:58:17.586754Z","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:d21a6dfd158000180678b1c6f47319930750da1c7de92cde51db7c13e40ab781","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":"2026-08-07T09:58:17.586754Z","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":"sha256:7432476f918bda30c07a9eae034a291e38cf73c4e82e72d15de01df1a9092818","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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":"sha256:3a34cf09213e30e7b36a911a03c212ab883edd3b02e45cc5aa7762e38714d63a","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":"2026-08-07T09:58:17.586754Z","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":"sha256:092b6e1cf1dba9bfcc50bb59e085a599d11076f479dddb5a3d97052075a07e84","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":"2026-08-07T09:58:17.586754Z","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:af356aaeca10a5378bb3d80588ad04c4b239e0814cd0e3689220c2009e89e6cf","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2026-08-07T09:58:17.586754Z","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":"sha256:266d39f30a407fad3033052350db6b097aef3ae34ee4f4965ad3802cac95900b","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":"2026-08-07T09:58:17.586754Z","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:c9df0bcbe47982b826ea3e4c98f1a3b1e826c67df8fdd2505fd7fb412f72b8d1","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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:ae887dda2401e0af64026693af0843838d2a5e8fb027824cfe2598ff3d1c3277","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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:bec2f959e946827c7ce52d36b56fe10188951db89d44eae5456b53760446bb36","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":"2026-08-07T09:58:17.586754Z","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:a7a68cec17610702ea9981547154d708d0809cc5b1d7a281ade450aff43dfa22","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":"2026-08-07T09:58:17.586754Z","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":"sha256:9629cbf10ea8f6c1b2547b03d2e54aa0912c2c6a3b17350be50c62e4825f4b37","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":"2026-08-07T09:58:17.586754Z","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":"sha256:7fb49f8dc48eb53d137b6b8d0928a91715ac63ca44c5c8df76ca299d5b1ce2ed","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04905","last_updated":"2025-03-20T03:28:56Z","snapshot_observed_at":"2026-08-07T18:33:21.332793Z","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":"2026-08-07T09:58:17.586754Z","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":"sha256:4eefb520e9b8a1cbc29c0e7b889fd44814886cf72a2fc27a181492ed616a826f","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":"2026-08-07T09:58:17.586754Z","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:b6eccd9005a601dd14743e5abf35363a7ebf34da00290506c6ce23ff2df46338","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":"2026-08-07T09:58:17.586754Z","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":"sha256:0832ca5cc7203e1bcdbbe7ca168f4b522c0d3720ea06f2a6e10a73b218257372","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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:cefd6730da5de92fb2aac703598c7f8fa6b5cf637421ef7cb0b7f4d374e5afc0","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":"2026-08-07T09:58:17.586754Z","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:f79b5e37eaf671e362113d1bb78978f0dd513371fc991444763c01cdc3ebf33a","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":"2026-08-07T09:58:17.586754Z","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":"sha256:22f7a03532e139611a61a0b295527f49c42c4872073e899b21ef6e504c7f13d1","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":"2026-08-07T09:58:17.586754Z","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":"sha256:5406878d7d22386d726af957b00839e0f335b5aff8abbc6f6960ce34f84da836","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":"2026-08-07T09:58:17.586754Z","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":"sha256:14c66d2f30fd1a15152935b9ee87d925058b465f05655891b1e76db80e8267e9","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":"2026-08-06T17:51:02.914236Z","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":"2026-08-07T09:58:17.586754Z","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:e06a21f60f820e04ff3999be1bf56432f8044a283970317719fe19154c9f884b","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":"2026-08-07T09:58:17.586754Z","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:cc4c463b1bb5786913357b9c0c04e3c135518d4850e132fc0d4a0e226a292582","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":"2026-07-06T19:40:21.797132Z","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":"2026-08-07T09:58:17.586754Z","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":"sha256:381d053319c78e8b4dcb17525598fc82711a034e56ae4c6f41880bacf01af189","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":"2026-08-07T09:58:17.586754Z","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:c5dd60a8ed6c9f3e38908f875452ff0954784986b0f400e8d54bde05676849eb","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":"2026-08-05T17:57:59.654845Z","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":"2026-08-07T09:58:17.586754Z","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":"sha256:46169dec38d80812e41e2a8cf43af9390c85d9032d23e7192affa54b09ebe663","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":"2026-08-03T06:35:03.018940Z","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":"2026-08-07T09:58:17.586754Z","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":"sha256:91f2b4d3891682f456bcb4ab464c7be998cf9f004aebbf0e1592e679721c96c8","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":"2026-08-07T09:58:17.586754Z","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:de81bd5b810263d1aef6d76ed28a0cee7cd4b4b06c90707eaf0967a5825f8310","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":"2026-08-07T09:58:17.586754Z","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:bae90b6cb9ea8ea0a63ea936670adf93cf476f824ac67d5869eafa948b07b312","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":"2026-08-07T09:58:17.586754Z","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":"sha256:5d4eb8548cfe517213c161bdd6493f239cad4bc4d97a84a9566e8312a46bd5fe","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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":"sha256:03ee4debd9e17e087abd42cf96ea53ed013926d64d81908b30e2c907fc0eb22c","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":"2026-08-07T09:58:17.586754Z","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":"sha256:22074790db895ed4c66436b279b4257215fdf4b0d17880a6b968c2d711962bcc","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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":"sha256:00bd3ec35653b26b9ec140ea04a7303e49a19421b9a478a99d7d62e584189495","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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":"sha256:9d16afdad2b639b6dbcc883bd751c424dbea15c763a0ed02bbd32094d348411b","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":"2026-08-07T09:58:17.586754Z","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":"sha256:7be44271a20555bd8cd74e0b65678379b06918406e1e97e3cb182be07f1b6db4","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":"2026-08-07T09:58:17.586754Z","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":"sha256:9d2a81acfc1adb19e7ec6e95cb086ede1ff91169e56a569cc2be996355d41466","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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:ab55747b3361ba99d8e880806d17fb88647855029bc8f8ccb9260710caa29796","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":"2026-08-07T09:58:17.586754Z","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":"sha256:870c3301a0c034ac1156a6372b5d55b7ba7ba768d99c99b8c38f6c9390926606","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":"2026-08-07T09:58:17.586754Z","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":"sha256:61471f5ca63109dcd66fc609a754921014bd0922ecde77c94beed06c96e7f071","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":"2026-08-07T09:58:17.586754Z","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":"sha256:767fbf50651e6710be2d1cc1b9ef242a9287dbf6774ace3535622b6994d806d5","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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":"sha256:079bf4abf2525dd44d1e6a834f2e28c36eca09f1cf41a18b06b82fe7346a917d","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":"2026-08-07T09:58:17.586754Z","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":"sha256:2bfb794aff82de4732db81433fafa718a6eba3ff8d8fc7b7a4b595b7eb7a9253","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":"2026-08-07T09:58:17.586754Z","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":"sha256:39caf1aeb054dbef43f0235f78f6ff01cf8915172f08476a0d118a42f0910f4d","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":"2026-08-02T11:40:55.318442Z","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":"2026-08-07T09:58:17.586754Z","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":"sha256:4a141193a3df394683fe428ab962aa247e4f761a5037416dcbaae84f9e2fbbc7","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":"2026-08-07T09:58:17.586754Z","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:f27de10708e68f5a0af83d3138c0c48dd1b0754eddf2373ed51d33e3b9368e40","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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":"sha256:0f3c8719acc1db9870d0abccd4d88322b39966d0a5119c03dfedec28b703da3a","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":"2026-08-07T09:58:17.586754Z","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":"sha256:889e2d9f9fce1c0eda779d8709a43b74e90ec8b380ed7c0e62c71ff75d3932bc","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":"2026-08-07T09:58:17.586754Z","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:de2c9598e34f59da3d0159aaaacb544c2ab21b6a9447fa2bc3272a117eda5c1d","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":"2026-08-07T09:58:17.586754Z","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:be5244d00e55d551a2afb52279d20b8f23ced71d55cbcedc6a4d57f58995bfc1","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":"2026-08-07T09:58:17.586754Z","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":"sha256:302221c0e064f599ee546c7e5a80322e6bfc56bd464fc72a1abe2af34992e346","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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:b5628679c4d28e1eeaba21981fab108e3b5a9c0cb5e912ca4be42f14f66f041f","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":"2026-08-07T09:58:17.586754Z","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:aead0908b4b0f3e765bfa10228fc959d7f731493bacbfc512bd68ba864997545","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":"2026-07-06T20:24:59.539207Z","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":"2026-08-07T09:58:17.586754Z","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":"sha256:8104526acf38cfa21bbe17fb03149c33f8df75b734437a45ecfd2f5153341f93","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":"2026-08-07T09:58:17.586754Z","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:a5d251bc11c5a875375e33b7541a2b2c7729dd84ffd8ac47f48500f2f9119c7d","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":"2026-08-07T09:58:17.586754Z","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":"sha256:14b44f5f17d4273d6a861a86819a049969ae86f12d06cb9119b23b456072b04c","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 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T09:58:17.586754Z","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:a0dd97acf5e35a0419d84f1fc8dd983ab42b4054fed7bf5461c96c7d1f1999ea","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":"2026-08-07T09:58:17.586754Z","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:d9957a5b2f6d5a5617d35ee5dadc473095d9267d22aa318c28a19beff436c9d3","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":"2026-08-07T09:58:17.586754Z","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:ba58e895e51cbfdd8019cec6b60a4d972aba9fccb0059a7b38c36b08fee610e3","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":"2026-08-07T09:58:17.586754Z","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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 3 inbound Pith citation observations for arXiv:2506.09003."}