109 citations · 288 across the 16 of their papers we have counts for
5 papers · 1 filter
IVR-R1: Refining Trajectories through Iterative Visual-Grounded Reasoning in Reinforcement Learning
Chenghao Li, Fusheng Hao, Xikai Zhang +5
Multimodal large language models via reinforcement learning (RL) have demonstrated remarkable capabilities in complex visual reasoning tasks, yet they remain limited in long-horizo…
Gated Coordination for Efficient Multi-Agent Collaboration in Minecraft Game
HuaDong Jian, Chenghao Li, Haoyu Wang +4
In long-horizon open-world multi-agent systems, existing methods often treat local anomalies as automatic triggers for communication. This default design introduces coordination no…
Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models
Xudong Wang, Chaoning Zhang, Chenghao Li +10
Large Language Models (LLMs) have demonstrated strong capabilities in complex reasoning tasks, while recent prompting strategies such as Chain-of-Thought (CoT) have further elevate…
Experience Transfer for Multimodal LLM Agents in Minecraft Game
Chenghao Li, Jun Liu, Songbo Zhang +7
Multimodal LLM agents operating in complex game environments must continually reuse past experience to solve new tasks efficiently. In this work, we propose Echo, a transfer-orient…
Efficient and Interpretable Multi-Agent LLM Routing via Ant Colony Optimization
Xudong Wang, Chaoning Zhang, Jiaquan Zhang +8
Large Language Model (LLM)-driven Multi-Agent Systems (MAS) have demonstrated strong capability in complex reasoning and tool use, and heterogeneous agent pools further broaden the…