Author

Chang Liu

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Preprint Aug 2026

SkillShapley: Boundary-Adaptive Shapley Valuation for Skill Step Attribution in LLM Agents

The proposed SkillShapley operates in two phases, motivated by key empirical insights, i.e., discretized benchmark rewards that create sharp performance cliffs, and step interactions that are largely additive rather than synergistic.

Chang Liu, Yu-Quan Zhang, Yiman Zhong et al. · 0 citations

Preprint Aug 2026

OptiMAS: Automatically Optimize Multi-Agent System

This work presents OptiMAS, a task-agnostic agentic optimizer that leverages textual interaction trajectories and task feedback as loss signals for end-to-end MAS evolution and sustains performance improvement over extended optimization horizons.

Yuxin Cheng, Chang Liu, Hanxin Yu et al. · 0 citations