5 papers
Optimize Once, Execute Fast: Latency-Aware Multi-Agent Workflow Learning for Recurrent Queries
Enpei Zhang, Feiyu Qu, Zheng Huang +3
Large Language Model-based Multi-Agent Systems (LLM-based MAS) have shown remarkable success in solving complex tasks by coordinating specialized agents through multi-step workflow…
Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints
Jiayu Li, Enpei Zhang, Dawei Zhou +2
We study workflow learning in a setting where specialized agents hand off control through a shared artifact, each agent observes only a local function of that artifact and its own…
One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL
Elynn Chen, Enpei Zhang, Jinhang Chai +1
We study online transfer reinforcement learning (RL) in episodic Markov decision processes, where experience from related source tasks is available during learning on a target task…
Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI
Zheng Huang, Enpei Zhang, Weikang Qiu +7
Understanding how the brain encodes visual information is a central challenge in neuroscience and machine learning. A promising approach is to reconstruct visual stimuli, essential…
Judging with Many Minds: Do More Perspectives Mean Less Prejudice? On Bias Amplifications and Resistance in Multi-Agent Based LLM-as-Judge
Chiyu Ma, Enpei Zhang, Yilun Zhao +7
LLM-as-Judge has emerged as a scalable alternative to human evaluation, enabling large language models (LLMs) to provide reward signals in trainings. While recent work has explored…