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cs.AI2026

SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents

Qingyao Li, Wenxiang Jiao, Shuai Shao +6

Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, while public libraries now hold thousands of them. Which skill to…

cs.AI2026

EnvACE: Internalizing Environment Dynamics via World Rehearsal for Agentic Reinforcement Learning

Zishan Xu, Zhiyuan Yao, Yuxin Chen +9

Training large language model agents for long-horizon tool use typically relies on interactions with real or synthesized executable environments, whose construction and verificatio…

cs.AI2026

Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories

Shuai Shao, Kangning Zhang, Qingyao Li +7

Agents built around large language models continually accumulate interaction trajectories during deployment, yet their behavior typically remains fixed. Beyond updating model weigh…

cs.AI2026

From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning

Beining Wu, Fuyou Mao, Jiong Lin +7

Generative engines (GEs) are reshaping information access by replacing ranked links with citation-grounded answers, yet current Generative Engine Optimization (GEO) methods optimiz…

cs.AI2026

ACE-Router: Generalizing History-Aware Routing from MCP Tools to the Agent Web

Zhiyuan Yao, Zishan Xu, Yifu Guo +6

With the rise of the Agent Web and Model Context Protocol (MCP), the agent ecosystem is evolving into an open collaborative network, exponentially increasing accessible tools. Howe…

cs.AI2025

SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning with LLM-Based Agents

Jiaye Lin, Yifu Guo, Yuzhen Han +11

Large Language Model (LLM)-based agents have recently shown impressive capabilities in complex reasoning and tool use via multi-step interactions with their environments. While the…