3 citations · 4 across the 10 of their papers we have counts for
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SWE-Prime: Fewer Trajectories, Better Performance
Dewu Zheng, Ruizhe Ye, Yanlin Wang +7
To improve large language models' ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory datasets and performing supervi…
Yet Even Less Is Even Better For Agentic, Reasoning, and Coding LLMs
CodeArts Model Team, Yang Ye, Jingyuan Tan +24
Training effective software engineering agents requires large volumes of task-specific trajectories, incurring substantial data construction costs. Inspired by the "Less-Is-More" h…
Structure-Aware Corpus Construction and User-Perception-Aligned Metrics for Large-Language-Model Code Completion
Dengfeng Liu, Jucai Zhai, Xiaoguang Jiang +8
Code completion technology based on large language model has significantly improved the development efficiency of programmers. However, in practical applications, there remains a g…