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cs.AI2026
Toward Anthropomorphic Dialogue: A Closed-Loop Framework for Human-Like Chat Generation, Evaluation, and Preference Alignment
Wentao Liu, Siyu Song, Xi Chen +4
Human-like private chat requires more than fluent response generation: a system must preserve persona, relationship, memory, bounded knowledge, medium-specific timing, and a cohere…
cs.AI2026
Multi-Agent Collaborative Reward Design for Enhancing Reasoning in Reinforcement Learning
Pei Yang, Ke Zhang, Ji Wang +5
We present CRM (Multi-Agent Collaborative Reward Model), a framework that replaces a single black-box reward model with a coordinated team of specialist evaluators to improve robus…
cs.AI2025
Beyond the Strongest LLM: Multi-Turn Multi-Agent Orchestration vs. Single LLMs on Benchmarks
Aaron Xuxiang Tian, Ruofan Zhang, Jiayao Tang +12
We study multi-turn multi-agent orchestration, where multiple large language model (LLM) agents interact over multiple turns by iteratively proposing answers or casting votes until…