19 citations · 30 across the 13 of their papers we have counts for
5 papers · 1 filter
ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning
Ziyu Wan, Yunxiang Li, Xiaoyu Wen +8
Recent research on Reasoning of Large Language Models (LLMs) has sought to further enhance their performance by integrating meta-thinking -- enabling models to monitor, evaluate, a…
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models
Jun Wang, Meng Fang, Ziyu Wan +10
In this technical report, we introduce OpenR, an open-source framework designed to integrate key components for enhancing the reasoning capabilities of large language models (LLMs)…
Reinforcing Language Agents via Policy Optimization with Action Decomposition
Muning Wen, Ziyu Wan, Weinan Zhang +2
Language models as intelligent agents push the boundaries of sequential decision-making agents but struggle with limited knowledge of environmental dynamics and exponentially huge…
Looking Ahead to Avoid Being Late: Solving Hard-Constrained Traveling Salesman Problem
Jingxiao Chen, Ziqin Gong, Minghuan Liu +3
Many real-world problems can be formulated as a constrained Traveling Salesman Problem (TSP). However, the constraints are always complex and numerous, making the TSPs challenging…
ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination
Xihuai Wang, Shao Zhang, Wenhao Zhang +4
Zero-shot coordination (ZSC) is a new cooperative multi-agent reinforcement learning (MARL) challenge that aims to train an ego agent to work with diverse, unseen partners during d…