{"as_of":"2026-08-10T00:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:24b7ebd99a6d474aa9327d20d299a2358d49b94ae1ef42e9927ffdf13ffce872","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":23,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T21:49:39.579721Z","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":"2026-07-05T07:20:46.348656Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-07T14:57:30.950099Z","title":"Swe-fixer: Training open-source llms for effective and efficient github issue resolution","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.16901","last_updated":"2025-06-23T20:05:49Z","snapshot_observed_at":"2026-08-09T22:54:53.685539Z","submitted_at":"2025-05-22T17:00:55Z","title":"Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks","version":4},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T14:57:30.950099Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2505.16901"},"observation_digest":"sha256:b8a542a86829f39c3a4210f05ea9157888197a15bcecc6883eb9d3c9388bc7d3","observation_id":"d1a44c8d-d7e8-4be6-8f41-79a80aa6961e","resolution":{"observed_at":"2026-08-07T14:57:30.950099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-07T12:50:04.636975Z","title":"Swe-fixer: Training open-source llms for effective and efficient github issue resolution.arXiv preprint arXiv:2501.05040, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.23419","last_updated":"2025-06-01T14:53:40Z","snapshot_observed_at":"2026-08-08T14:28:49.134889Z","submitted_at":"2025-05-29T13:09:44Z","title":"SWE-bench Goes Live!","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T12:50:04.636975Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2505.23419"},"observation_digest":"sha256:4612eb2084ad78125ad8f91c01eb4f77e1e24bc123574c5835b538f702f9d7aa","observation_id":"925eeec0-5829-427d-8f13-bb0404cd028d","resolution":{"observed_at":"2026-08-07T12:50:04.636975Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-07T12:47:22.735606Z","title":"Swe- fixer: Training open-source llms for effective and efficient github issue resolution, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.23604","last_updated":"2025-05-29T16:15:36Z","snapshot_observed_at":"2026-08-09T05:03:49.842579Z","submitted_at":"2025-05-29T16:15:36Z","title":"Satori-SWE: Evolutionary Test-Time Scaling for Sample-Efficient Software Engineering","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T12:47:22.735606Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2505.23604"},"observation_digest":"sha256:f4fef8933067d5db38c9c56ae4ff389f1efe15abde44369dd6a212a810a2dd99","observation_id":"b8a8da2d-68e5-40e2-9c27-5302e4dda0e6","resolution":{"observed_at":"2026-08-07T12:47:22.735606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-07T04:16:08.461930Z","title":"Swe- fixer: Training open-source llms for effective and efficient github issue resolution.ArXiv, abs/2501.05040, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.11425","last_updated":"2025-06-20T23:32:06Z","snapshot_observed_at":"2026-08-09T19:01:30.828855Z","submitted_at":"2025-06-13T02:46:53Z","title":"Agent-RLVR: Training Software Engineering Agents via Guidance and Environment Rewards","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T04:16:08.461930Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2506.11425"},"observation_digest":"sha256:1997d33055be53a946cab94cddf4f76ffb3033f50bf8f5b385e8dd9bdeddec5f","observation_id":"0d47d712-a232-45d9-8689-ce8afc3db309","resolution":{"observed_at":"2026-08-07T04:16:08.461930Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-07T00:49:34.867693Z","title":"SWE- Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.12728","last_updated":"2025-06-15T05:42:01Z","snapshot_observed_at":"2026-08-09T00:45:48.015242Z","submitted_at":"2025-06-15T05:42:01Z","title":"MCTS-Refined CoT: High-Quality Fine-Tuning Data for LLM-Based Repository Issue Resolution","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T00:49:34.867693Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2506.12728"},"observation_digest":"sha256:86558e907c1e1bd46c35a966d153a438766457a54e73b2957be3b2786cb5dc66","observation_id":"304004a8-5abd-4589-9031-288696c97741","resolution":{"observed_at":"2026-08-07T00:49:34.867693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-06T23:11:10.148823Z","title":"Swe-fixer: Training open-source llms for effective and efficient github issue resolution.arXiv preprint arXiv:2501.05040,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.19290","last_updated":"2025-06-24T03:53:36Z","snapshot_observed_at":"2026-08-09T21:24:15.552941Z","submitted_at":"2025-06-24T03:53:36Z","title":"Skywork-SWE: Unveiling Data Scaling Laws for Software Engineering in LLMs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T23:11:10.148823Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2506.19290"},"observation_digest":"sha256:d3f219113ba6dc86a73d92e5022edbac7313c153f7a44374e678c71dc281b3c1","observation_id":"1bf4f200-d3c6-439a-b088-c3355b62f43c","resolution":{"observed_at":"2026-08-06T23:11:10.148823Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-06T16:54:58.625857Z","title":"Swe-fixer: Training open-source llms for effective and efficient github issue resolution","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":22,"source":"arxiv_source","source_observed_at":"2026-08-06T16:54:58.625857Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2507.12415"},"observation_digest":"sha256:3832c5c068e162f079f0b110356cd26ca35669ed9e68427d1bacf776586fcd44","observation_id":"3b6fe600-7ed3-4494-8f9a-c2d6ce3cadff","resolution":{"observed_at":"2026-08-06T16:54:58.625857Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-06T14:43:14.356628Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18130","last_updated":"2025-08-18T15:26:59Z","snapshot_observed_at":"2026-08-08T07:09:28.375868Z","submitted_at":"2025-07-24T06:38:19Z","title":"NoCode-bench: A Benchmark for Evaluating Natural Language-Driven Feature Addition","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T14:43:14.356628Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2507.18130"},"observation_digest":"sha256:4131b3df5715d866b03f94b694e0e73ddb4b447ba1ccb4e5191dc63092f42b92","observation_id":"73f451ca-e7b1-4a5d-88d0-9cad2f3648f7","resolution":{"observed_at":"2026-08-06T14:43:14.356628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-03T07:17:13.457928Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.20789","last_updated":"2026-05-29T01:36:45Z","snapshot_observed_at":"2026-08-06T06:19:33.132630Z","submitted_at":"2026-01-28T17:27:08Z","title":"SERA: Soft-Verified Efficient Repository Agents","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T07:17:13.457928Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2601.20789"},"observation_digest":"sha256:ec647367fa75ccff3ee15cf37b0bb98d81af7fb2ea90cdc7134fdbdba9bb6eee","observation_id":"18eaafac-43e0-4b41-b261-734a35fd9407","resolution":{"observed_at":"2026-08-03T07:17:13.457928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-03T06:22:26.970018Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.22956","last_updated":"2026-07-04T09:14:30Z","snapshot_observed_at":"2026-08-06T02:36:25.299827Z","submitted_at":"2026-01-30T13:17:14Z","title":"SWE-Manager: Selecting and Synthesizing Golden Proposals Before Coding","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T06:22:26.970018Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2601.22956"},"observation_digest":"sha256:0c07ac351362ff01db9f39a8a62605e1d63a4f3a3a32cd94cb9db81751cc7c52","observation_id":"513c02c2-fb79-4295-8b85-3350d7cd92ab","resolution":{"observed_at":"2026-08-03T06:22:26.970018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-03T06:13:01.657492Z","title":"Swe-fixer: Training open-source llms for effective and efficient github issue resolution.arXiv preprint arXiv:2501.05040, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.23257","last_updated":"2026-05-27T23:46:30Z","snapshot_observed_at":"2026-08-05T01:50:54.147116Z","submitted_at":"2026-01-30T18:25:39Z","title":"From Historical Patches to Repair Plans: Outcome-Conditioned Reasoning for Repository-Level Program Repair","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T06:13:01.657492Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2601.23257"},"observation_digest":"sha256:f6baeb1e1b21274eb5821d5e3d20de562bb73eabfeb237ce0f2e7621cc4cf91f","observation_id":"ca1600cc-1a13-4380-be7e-930904d1137e","resolution":{"observed_at":"2026-08-03T06:13:01.657492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":"2501.05040","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-05T07:20:46.348656Z","title":"SWE-Fixer : Training open-source LLMs for effective and efficient GitHub issue resolution","venue":null,"work_id":"d6bee59c-bb1e-4708-9584-81e6d7306cf0","year":2025},"citing_paper":{"arxiv_id":"2604.19741","last_updated":"2026-06-03T18:09:47Z","snapshot_observed_at":"2026-08-01T19:25:06.120681Z","submitted_at":"2026-04-21T17:59:03Z","title":"CityRAG: Stepping Into a City via Spatially-Grounded Video Generation","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-07-05T07:19:01.989427Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2604.19741"},"observation_digest":"sha256:071580ecbba54bb598e0ab46c7217847ad2e13ff1bd30b0b07ba9264b84e0edb","observation_id":"8ffdf682-11e9-4486-896f-744a4061a0d4","resolution":{"observed_at":"2026-07-05T07:20:46.351775Z","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":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":"2501.05040","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-05T07:20:46.348656Z","title":"SWE-Fixer : Training open-source LLMs for effective and efficient GitHub issue resolution","venue":null,"work_id":"d6bee59c-bb1e-4708-9584-81e6d7306cf0","year":2025},"citing_paper":{"arxiv_id":"2604.19742","last_updated":"2026-04-21T17:59:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-21T17:59:16Z","title":"PlayCoder: Making LLM-Generated GUI Code Playable","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-10T02:02:01.395176Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2604.19742"},"observation_digest":"sha256:30c73254b1247105e1c40bcf3695abe6784a368bdf4017958e7716e16ff8ef02","observation_id":"d67a85d4-8d4c-4327-8c07-15ee76799776","resolution":{"observed_at":"2026-05-11T13:16:18.439395Z","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":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":"2501.05040","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-05T07:20:46.348656Z","title":"SWE-Fixer : Training open-source LLMs for effective and efficient GitHub issue resolution","venue":null,"work_id":"d6bee59c-bb1e-4708-9584-81e6d7306cf0","year":2025},"citing_paper":{"arxiv_id":"2605.09134","last_updated":"2026-05-13T16:38:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-09T19:31:02Z","title":"BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models","version":1},"reference_index":107,"source":"arxiv_source","source_observed_at":"2026-05-12T03:09:40.321500Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2605.09134"},"observation_digest":"sha256:a0cfcedbaa262e35beae66ccaff1f4e235fdd00a0d8ae3f358bbf06b5b2f8dfd","observation_id":"2592e9f1-b52b-493b-878b-c552ba4d3219","resolution":{"observed_at":"2026-05-12T03:11:18.952817Z","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":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":"2501.05040","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-05T07:20:46.348656Z","title":"SWE-Fixer : Training open-source LLMs for effective and efficient GitHub issue resolution","venue":null,"work_id":"d6bee59c-bb1e-4708-9584-81e6d7306cf0","year":2025},"citing_paper":{"arxiv_id":"2605.09134","last_updated":"2026-05-13T16:38:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-09T19:31:02Z","title":"BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models","version":2},"reference_index":119,"source":"arxiv_source","source_observed_at":"2026-05-13T06:03:32.270553Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2605.09134"},"observation_digest":"sha256:74a7fb9981782aafb4e8c4cd39b92ac47765ef8274af3a1013946b44da4ccf09","observation_id":"f7a7da30-7015-4d00-9fe9-5e06abf203a4","resolution":{"observed_at":"2026-05-13T06:07:22.388044Z","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":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":"2501.05040","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-05T07:20:46.348656Z","title":"SWE-Fixer : Training open-source LLMs for effective and efficient GitHub issue resolution","venue":null,"work_id":"d6bee59c-bb1e-4708-9584-81e6d7306cf0","year":2025},"citing_paper":{"arxiv_id":"2606.00750","last_updated":"2026-05-30T14:34:02Z","snapshot_observed_at":"2026-07-06T23:41:24.911421Z","submitted_at":"2026-05-30T14:34:02Z","title":"I-WebGenBench : Evaluating Interactivity in LLM-Generated Scientific Web Applications","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-28T18:53:18.645984Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2606.00750"},"observation_digest":"sha256:57a97e0f249928ff249ba4d5088e89076130b2d8684ab45e06ddd7ba2db7909a","observation_id":"47d294e6-c3d3-4842-ba1b-7d0fcd29bf32","resolution":{"observed_at":"2026-06-28T19:42:36.268744Z","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":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":"2501.05040","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-05T07:20:46.348656Z","title":"SWE-Fixer : Training open-source LLMs for effective and efficient GitHub issue resolution","venue":null,"work_id":"d6bee59c-bb1e-4708-9584-81e6d7306cf0","year":2025},"citing_paper":{"arxiv_id":"2606.03461","last_updated":"2026-06-02T10:37:47Z","snapshot_observed_at":"2026-07-06T23:43:40.769504Z","submitted_at":"2026-06-02T10:37:47Z","title":"What Makes Interaction Trajectories Effective for Training Terminal Agents?","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-28T10:17:26.880381Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2606.03461"},"observation_digest":"sha256:44465fd6d37f85238890fcafabae5af435ec986520e182c7ec04ddc47b86c5e8","observation_id":"86135994-2d82-47fb-84f0-aab0c3560f6a","resolution":{"observed_at":"2026-07-02T03:06:30.352803Z","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":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":"2501.05040","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-05T07:20:46.348656Z","title":"SWE-Fixer : Training open-source LLMs for effective and efficient GitHub issue resolution","venue":null,"work_id":"d6bee59c-bb1e-4708-9584-81e6d7306cf0","year":2025},"citing_paper":{"arxiv_id":"2606.09659","last_updated":"2026-06-08T15:43:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-06-08T15:43:16Z","title":"End-to-End Context Compression at Scale","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-06-27T16:36:54.699174Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2606.09659"},"observation_digest":"sha256:a099bc9ba3efb6ee55b61d43b6e94ac3a6c23c5f93a64714497b0f3868587b74","observation_id":"1163e25a-3b26-4af9-9ddd-a9d519041c28","resolution":{"observed_at":"2026-07-03T01:17:31.558821Z","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":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-07-14T07:26:27.360126Z","title":"://arxiv.org/abs/2501.05040, 2501.05040","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.11046","last_updated":"2026-07-13T03:18:22Z","snapshot_observed_at":"2026-08-07T15:19:45.601808Z","submitted_at":"2026-07-13T03:18:22Z","title":"Retrieval-Oriented Code Representations in Agentic Bug Localization","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-07-14T07:26:27.360126Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2607.11046"},"observation_digest":"sha256:8bcf5af4a612ad2723a5155cc844139ce16faf77ad9d29a4d14a0d176e18507c","observation_id":"3c6993aa-5948-4cf9-ae35-ca315cb06c30","resolution":{"observed_at":"2026-07-14T07:26:27.360126Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-01T18:36:17.933726Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17286","last_updated":"2026-07-19T15:08:08Z","snapshot_observed_at":"2026-08-09T23:04:15.415274Z","submitted_at":"2026-07-19T15:08:08Z","title":"IssueExec: A Test-Driven Approach for Localizing Software Engineering Issues","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-01T18:36:17.933726Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2607.17286"},"observation_digest":"sha256:449284359037509a75785938a5e5ed04c1d710db9b4ddac7ab6ded3e658b344b","observation_id":"73170867-4d5a-40d4-86eb-86406d852bc2","resolution":{"observed_at":"2026-08-01T18:36:17.933726Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-01T14:11:58.501423Z","title":"Swe- fixer: Training open-source llms for effective and efficient github issue resolution,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.18859","last_updated":"2026-07-21T08:49:30Z","snapshot_observed_at":"2026-08-08T05:58:51.576912Z","submitted_at":"2026-07-21T08:49:30Z","title":"PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-01T14:11:58.501423Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2607.18859"},"observation_digest":"sha256:498eae3dfef9119d3da5191cf9d37faa47f8de1a8a0367339fa0c64e92c20a52","observation_id":"2370ef1a-7e5a-4fb0-a605-fd0265ccd270","resolution":{"observed_at":"2026-08-01T14:11:58.501423Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-06T16:21:10.867962Z","title":"SWE-Fixer: Training open-source LLMs for effective and efficient GitHub issue resolution,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.04804","last_updated":"2026-08-05T13:11:31Z","snapshot_observed_at":"2026-08-08T23:13:12.927485Z","submitted_at":"2026-08-05T13:11:31Z","title":"Scrouting: Cost-Aware Routing of Coding Agents by Scouting the Repository First","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:21:10.867962Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2608.04804"},"observation_digest":"sha256:d60d66232d901ed1742151dbe6cbbc413d178d19d26074f7b0b2941bf2c10b50","observation_id":"66144ce3-fc94-4c1b-8d9f-feb15afd81a5","resolution":{"observed_at":"2026-08-06T16:21:10.867962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.05040","snapshot_observed_at":"2026-08-07T21:49:39.579721Z","title":"An Yang et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05886","last_updated":"2026-08-06T11:07:42Z","snapshot_observed_at":"2026-08-09T23:11:47.010634Z","submitted_at":"2026-08-06T11:07:42Z","title":"CodeGrep: An RL-Trained Retrieval Agent for LLM Coding Agents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T21:49:39.579721Z"},"links":{"cited_paper":"/paper/2501.05040","citing_paper":"/paper/2608.05886"},"observation_digest":"sha256:551bfc6f39f49c6282c70970c382c93600d17d860b1dff3f4eaffe5984e59de1","observation_id":"a8219774-6e1e-46d6-a60b-ae7aa2e4f535","resolution":{"observed_at":"2026-08-07T21:49:39.579721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2501.05040/citation-record","integrity":"/paper/2501.05040/integrity","json":"/paper/2501.05040/citation-record.json","paper":"/paper/2501.05040"},"outbound":[],"paper":{"arxiv_id":"2501.05040","last_updated":"2025-05-07T04:06:41Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T14:17:37.281562Z","submitted_at":"2025-01-09T07:54:24Z","title":"SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2501.05040."}