collaborators

12 papers

cs.MM2026

MPrune: Hierarchical Collaborative Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation

Taolin Zhang, Weizi shao, Zijie Zhou +5

Recent advances in multi-modal retrieval-augmented generation (mRAG), which augments multi-modal large language models (MLLMs) with external knowledge, have shown that collective i…

cs.CL2026

Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains

Taolin Zhang, Zijie Zhou, Jiuheng Wan +4

Large language model (LLM)-based multi-agent systems have shown strong potential for complex reasoning by coordinating specialized agents through structured communication. However,…

cs.CL2026

AMATA: Adaptive Multi-Agent Trajectory Alignment for Knowledge-Intensive Question Answering

Taolin Zhang, Dongyang Li, Chen Chen +5

Despite substantial advances in large language models (LLMs), generating factually consistent responses for knowledge-intensive question answering remains challenging. These diffic…

cs.CL2026

Taming "Zombie'' Agents: A Markov State-Aware Framework for Resilient Multi-Agent Evolution

Taolin Zhang, Pukun Zhao, Qizhou Chen +5

Recent advancements in LLM-based multi-agent systems have demonstrated remarkable collaborative capabilities across complex tasks. To improve overall efficiency, existing methods o…

cs.CL2025

An Information-Theoretic Framework for Robust Large Language Model Editing

Qizhou Chen, Chengyu Wang, Taolin Zhang +1

Large Language Models (LLMs) have become indispensable tools in science, technology, and society, enabling transformative advances across diverse fields. However, errors or outdate…

cs.AI2025

MPrune: Hierarchical Communication Graph Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation

Weizi Shao, Taolin Zhang, Zijie Zhou +3

Recent advancements in multi-modal retrieval-augmented generation (mRAG), which enhance multi-modal large language models (MLLMs) with external knowledge, have demonstrated that th…