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cs.AI2026
AlphaDiana: A Measurement System for Agents in Verifiable Reasoning Tasks
Zhanke Zhou, Zongze Li, Weikai Huang +16
Agents pair reasoning models with harnesses that organize model calls, execute tools, load skill instructions, and retain history in memory. Understanding agent performance require…
cs.LG2026
DICE: Entropy-Regularized Equilibrium Selection for Stable Multi-Agent LLM Coordination
Yi Xie, Zhanke Zhou, Chentao Cao +2
Multi-agent large language model (LLM) systems often fail to reliably outperform a single strong model equipped with best-of-N sampling. We argue that a core source of this instabi…
cs.LG2026
The Easy, the Hard, and the Learnable: Confidence and Difficulty-Adaptive Policy Optimization for LLM Reasoning
Zhanke Zhou, Xiangyu Lu, Chentao Cao +4
RL with verifiable rewards can substantially improve LLM reasoning, yet standard GRPO-style training often treats easy, hard, and learnable questions alike through uniform sampling…