1 citations · 1 across the 3 of their papers we have counts for
6 papers
The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems
Xiaoze Liu, Ruowang Zhang, Weichen Yu +7
Multi-Agent Systems (MAS) powered by Large Language Models have unlocked advanced collaborative reasoning, yet they remain bottlenecked by discrete text communication, which impose…
PORTool: Importance-Aware Policy Optimization with Rewarded Tree for Multi-Tool-Integrated Reasoning
Feijie Wu, Weiwu Zhu, Yuxiang Zhang +5
Multi-tool-integrated reasoning enables LLM-empowered tool-use agents to solve complex tasks by interleaving natural-language reasoning with calls to external tools. However, train…
Talk to Right Specialists: Iterative Routing in Multi-agent Systems for Question Answering
Feijie Wu, Zitao Li, Fei Wei +3
Retrieval-augmented generation (RAG) agents are increasingly deployed to answer questions over local knowledge bases that cannot be centralized due to knowledge-sovereignty constra…
Bohrium + SciMaster: Building the Infrastructure and Ecosystem for Agentic Science at Scale
Linfeng Zhang, Siheng Chen, Yuzhu Cai +46
AI agents are emerging as a practical way to run multi-step scientific workflows that interleave reasoning with tool use and verification, pointing to a shift from isolated AI-assi…
Generating Millions Of Lean Theorems With Proofs By Exploring State Transition Graphs
David Yin, Jing Gao
Large Language Models (LLMs) have demonstrated significant potential in generating mathematical proofs. However, a persistent challenge is that LLMs occasionally make mistakes, whi…
How Can LLMs and Knowledge Graphs Contribute to Robot Safety? A Few-Shot Learning Approach
Abdulrahman Althobaiti, Angel Ayala, JingYing Gao +4
Large Language Models (LLMs) are transforming the robotics domain by enabling robots to comprehend and execute natural language instructions. The cornerstone benefits of LLM includ…