SWE-smith: Scaling Data for Software Engineering Agents
机构 * Stanford University(斯坦福大学) ; Princeton University(普林斯顿大学) ; Alibaba Qwen(阿里巴巴文言)
Comments All assets available at https://swesmith.com
作者
Natural Language Processing
机构 * Stanford University(斯坦福大学) ; Princeton University(普林斯顿大学) ; Alibaba Qwen(阿里巴巴文言)
Comments All assets available at https://swesmith.com
机构 * SCB 10X, SCBX Group(SCB 10X、SCBX集团) ; University of Southern California(南加州大学) ; Stanford University(斯坦福大学)
机构 * Dartmouth College(达特茅斯学院) ; Adobe Research(Adobe研究) ; Stanford University(斯坦福大学) ; University of Massachusetts Amherst(马萨诸塞大学阿默斯特分校) ; Pattern Data ; Vanderbilt University(范德比尔特大学) ; Dolby Research(Dolby研究) ; University of California San Diego(加州大学圣地亚哥分校) ; Cisco Research(思科研究) ; University of Oregon(俄勒冈大学)
Comments Accepted at the Transactions on Machine Learning Research (TMLR) journal
机构 * Stanford University(斯坦福大学)
Comments main paper is 14 pages
Comments V4, fixes to title and formatting
机构 * Princeton Language and Intelligence(普林斯顿语言与智能研究所) ; Stanford University(斯坦福大学) ; OpenAI(开放人工智能研究所)
Comments For code, data, visualizer, visit: https://kite-live.vercel.app
机构 * Stanford University(斯坦福大学) ; Georgia Institute of Technology(佐治亚理工学院)
Comments ACL 2025 Main Conference
机构 * Georgia Tech(佐治亚理工学院) ; The University of Hong Kong(香港大学) ; Stanford University(斯坦福大学)
Comments ACL 2025
Comments Preprint, 23 pages, 14 figures. Project page at https://salt-nlp.github.io/GEP/
Journal ref EAAMO '24: Proceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, 2024
机构 * University of Wisconsin-Madison(威斯康星大学麦迪逊分校) ; Indiana University Indianapolis(印第安纳大学印第安纳波利斯分校) ; Stanford University(斯坦福大学)
机构 * Stanford University(斯坦福大学) ; USC(美国南加州大学)
Comments ICLR 2025; 28 pages, 8 figures
Comments 75 pages
Comments NeurIPS 2024 Datasets and Benchmarks Track
Comments 45 pages, 14 figures, CSCW 2025
Comments pre-MIT Press publication version
Comments NAACL 2025; The first two authors contributed equally
Comments Published in COLM2024. Code Repo: https://github.com/SALT-NLP/DyLAN
Comments Accepted at NeurIPS 2024 Track Datasets & Benchmarks Track
Comments preprint, 9 pages
Comments EMNLP 2024
Comments 9 pages, 10 figures, In Findings of EMNLP 2024
Comments main paper is 20 pages
Comments CSCW 2024