4 citations · 5 across the 16 of their papers we have counts for
5 papers · 1 filter
MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning
Yaolun Zhang, Yujie Zhao, Nan Wang +6
Automatic multi-agent systems aim to instantiate agent workflows without relying on manually designed or fixed orchestration. However, existing automatic MAS approaches remain only…
EVOCHAMBER: Test-Time Co-evolution of Multi-Agent System at Individual, Team, and Population Scales
Yaolun Zhang, Tianyi Xu, Shengyu Dai +3
We argue that multi-agent test-time evolution is not single-agent evolution replicated N times. A single-agent learner can only evolve its own context and memory. A multi-agent sys…
Live-Evo: Online Evolution of Agentic Memory from Continuous Feedback
Yaolun Zhang, Yiran Wu, Yijiong Yu +2
Large language model (LLM) agents are increasingly equipped with memory, which are stored experience and reusable guidance that can improve task-solving performance. Recent \emph{s…
MetaAgent: Automatically Constructing Multi-Agent Systems Based on Finite State Machines
Yaolun Zhang, Xiaogeng Liu, Chaowei Xiao
Large Language Models (LLMs) have demonstrated the ability to solve a wide range of practical tasks within multi-agent systems. However, existing human-designed multi-agent framewo…
From Unstructured Communication to Intelligent RAG: Multi-Agent Automation for Supply Chain Knowledge Bases
Yao Zhang, Zaixi Shang, Silpan Patel +1
Supply chain operations generate vast amounts of operational data; however, critical knowledge such as system usage practices, troubleshooting workflows, and resolution techniques…