43 citations · 52 across the 9 of their papers we have counts for
4 papers · 1 filter
MAS-Gate: Unlocking Multi-Agent System Lifecycle via Node-Centric Quantification
Hehai Lin, Zixuan Wang, Ming Yan +6
Large language model (LLM)-based multi-agent systems (MAS) can solve complex problems beyond the reach of a single agent by decomposing tasks and coordinating complementary capabil…
Unified-MAS: Universally Generating Domain-Specific Nodes for Empowering Automatic Multi-Agent Systems
Hehai Lin, Yu Yan, Zixuan Wang +6
Automatic Multi-Agent Systems (MAS) generation has emerged as a promising paradigm for solving complex reasoning tasks. However, existing frameworks are fundamentally bottlenecked…
Interactive Learning for LLM Reasoning
Hehai Lin, Shilei Cao, Sudong Wang +5
Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large Language Models (LLMs), thereby c…
A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems
Zixuan Ke, Fangkai Jiao, Yifei Ming +9
Reasoning is a fundamental cognitive process that enables logical inference, problem-solving, and decision-making. With the rapid advancement of large language models (LLMs), reaso…