arXiv:2610.09430v1 Announce Type: new
Abstract: Internalizing external skills changes a language agent's capabilities and, with them, the value of its remaining guidance: rules can become redundant,...
By Ling Li, Qiuyu Shen, Zheng Jiang, Qinwei Ma, Yuxuan Liu, Zhidong Deng
arXiv:2608.22610v1 Announce Type: new
Abstract: Agent skills, structured artifacts distilled from interaction trajectories and dynamically reused from skill banks, have become a central mechanism for...
By Qiyan Zhao, Xiaofeng Zhang, Bo Liu, Minda Chen, Wei Xiong, Jingyang Chen, Guanting Ye, Wenhao Yu, Xiaosong Yuan, Shijie Han, Da-Han Wang, Jianmin Ji, Fei Huang, Xu-Yao Zhang
Agent skills, structured artifacts distilled from interaction trajectories and dynamically reused from skill banks, have become a central mechanism for enabling large language model (LLM)-based self-e...
arXiv:2608. 02636v1 Announce Type: cross Abstract: Self-evolving skill systems promise to improve agents by turning execution feedback into persistent skill updates without changing the underlying model.
By Yuxuan Liu, Zhaochen Su, Yuhao Zhang, Jiahe Guo, Zhongwei Xie, Huihao Jing, Lingyun Xie, Qing Zong, Yauwai Yim, Zhixiong Zhang, Haoran Li, Yangqiu Song
arXiv:2607. 12790v1 Announce Type: new Abstract: Self-evolving agent systems improve by creating, revising, and retiring their own skills, but every such loop rests on a hidden assumption: a reliable evaluation metric already exists.
By Xing Zhang, Guanghui Wang, Yanwei Cui, Ziyuan Li, Wei Qiu, Bing Zhu, Peiyang He
The paper audits self‑evolving financial agents—SkillOpt, Agent Workflow Memory (AWM), and ReasoningBank—by evaluating their performance, security drift, and execution‑interface mismatches in simulated e‑banking scenarios. It shows that while utility improves after evolution, exposure to malicious content and unauthorized state changes also rise, and that AWM’s text‑action envelope can disrupt tool execution, highlighting the need for comprehensive auditing beyond accuracy metrics.
By Jialong Li, Jialing Zhu