3 citations · 4 across the 5 of their papers we have counts for
4 papers · 1 filter
MASBench: Benchmarking LLM-based Multi-Agent Collaboration under Partial Observability
Qizhi Chu, Zekai Yu, Sijie Wen +5
Large language models (LLMs) have progressively evolved into the core of autonomous agents. Building on this progress, LLM-based multi-agent systems (MAS) coordinate multiple agent…
ParaTool: Shifting Tool Representations from Context to Parameters
Zekai Yu, Qi Meng, Qizhi Chu +3
Tool calling extends large language models (LLMs) by enabling grounded interaction with external executable interfaces, thereby supporting environment-coupled problem solving. Howe…
GraphTeam: Facilitating Large Language Model-based Graph Analysis via Multi-Agent Collaboration
Xin Li, Qizhi Chu, Yubin Chen +7
Graphs are widely used for modeling relational data in real-world scenarios, such as social networks and urban computing. Existing LLM-based graph analysis approaches either integr…
Leveraging Large Language Models for Relevance Judgments in Legal Case Retrieval
Shengjie Ma, Qi Chu, Jiaxin Mao +3
Determining which legal cases are relevant to a given query involves navigating lengthy texts and applying nuanced legal reasoning. Traditionally, this task has demanded significan…