Recently, coding agents have emerged as a dominant paradigm for real-world software engineering (SWE) scenarios, which solve complex tasks through multi-turn interactions with development environments. However, frequent interactions with environments would inevitably introduce substantial token overhead, leading to hig...
Hao-Bin Li, Liang Jiang, Zhen-Yu Huang et al.· 0 citations
Effective skill identification is crucial for LLM agents to reuse task-solving experience for complex task execution, which however remains challenging as agents must accurately identify useful skills from a large skill gallery and invoke them on demand. Existing studies have explored various strategies for skill retri...
Shuo Liu, Yu-Tong Yang, Haonan Xiao et al.· 2 citations
This work proposes SkillDreamer, a novel framework that first infers the capabilities necessary for task execution, then imagines how to realize these capabilities by generating pseudo skills, and finally leverages such prospective information to bridge the gap between objective-oriented task queries and execution-orie...
Shuo Liu, Yu-Tong Yang, Haonan Xiao et al.· 3 citations
This work proposes a novel difficulty-aware task formulation pipeline with a dual-track evaluation framework, facilitating comprehensive evaluation of proactive bug-fixing capability, and proposes a novel difficulty-aware task formulation pipeline with a dual-track evaluation framework.
Hao-Bin Li, Ping Deng, Weizhong Qian et al.· 0 citations
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