From the 1 of 27 linked papers with an AI index.
9 papers · 1 filter
SWE-RM: Execution-free Feedback For Software Engineering Agents
KaShun Shum, Binyuan Hui, Jiawei Chen +6
Execution-based feedback like unit testing is widely used in the development of coding agents through test-time scaling (TTS) and reinforcement learning (RL). This paradigm require…
VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos
Dunjie Lu, Yiheng Xu, Junli Wang +12
Training computer-use agents requires massive amounts of GUI interaction data, but manually annotating action trajectories at scale is prohibitively expensive. We present VideoAgen…
Towards Better Correctness and Efficiency in Code Generation
Yunlong Feng, Yang Xu, Xiao Xu +2
While code large language models have demonstrated remarkable progress in code generation, the generated code often exhibits poor runtime efficiency, limiting its practical applica…
IFEvalCode: Controlled Code Generation
Jian Yang, Wei Zhang, Shukai Liu +9
Code large language models (Code LLMs) have made significant progress in code generation by translating natural language descriptions into functional code; however, real-world appl…
Turning the Tide: Repository-based Code Reflection
Wei Zhang, Jian Yang, Jiaxi Yang +5
Code large language models (LLMs) enhance programming by understanding and generating code across languages, offering intelligent feedback, bug detection, and code updates through…
SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner
Lei Zhang, Jiaxi Yang, Min Yang +6
We introduce **SWE-Flow**, a novel data synthesis framework grounded in Test-Driven Development (TDD). Unlike existing software engineering data that rely on human-submitted issues…