Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing errors without breaking correct behavior. Existing benchmarks do not systematically distinguish documentation repair, script repair, and preservation when evaluating skill s...
Yuxuan Liu, Hao-Ran Li, Yu-Hao Zhang et al.· 0 citations
This work proposes soft-target fine-tuning (SoFT) to balance learning from teacher demonstrations with retaining the Base model's existing capabilities, with improvements in both in-distribution capability acquisition and out-of-distribution generalization.
Hui-Hao Jing, Wen-Bin Hu, Shao-Jin Chen et al.· 0 citations
A cross-modal grounding study shows that text-level VCI ordering largely survives faithful rendering and blind image-level preference judgment, supporting Ekphrasis as a measure of visual ideation beyond prose quality.
Hongyu Luo, Hexi Wang, Hui-Hao Jing et al.· 0 citations
Results indicate that MultivationBench presents a significant challenge: all tested models struggle to maintain consistent motivation reasoning across sequential contexts, revealing a critical disconnect between static recognition capabilities and the dynamic reasoning essential for human-like social understanding.
This survey focuses on co-evolution in agentic systems, a multi-component form of self-evolution in which multiple agents and their environment impose adaptive pressure on one another.
Qing Zong, Jiayu Liu, Junhao Shen et al.· 0 citations
Overall, persistent skill self-evolution is better understood as sparse, validation-filtered search with model- and benchmark-dependent returns, rather than steady improvement from additional rounds.
Yuxuan Liu, Zhaochen Su, Yuhao Zhang et al.· 2 citations
This work proposes RLPF, reinforcement learning from performance feedback, which turns execution outcomes into a staged reward, and suggests that code agents can be trained not only to pass tests, but also to optimize the programs they write.
Huihao Jing, Hao-Zhe Cui, Wenbin Hu et al.· arXiv.org· 0 citations
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