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cs.CL2026
Attention-MoA: Enhancing Mixture-of-Agents via Inter-Agent Semantic Attention and Deep Residual Synthesis
Jianyu Wen, Yang Wei, Xiongxi Yu +2
As the development of Large Language Models (LLMs) shifts from parameter scaling to inference-time collaboration, the Mixture-of-Agents (MoA) framework has emerged as a general par…
cs.CL2025
USB-Rec: An Effective Framework for Improving Conversational Recommendation Capability of Large Language Model
Jianyu Wen, Jingyun Wang, Cilin Yan +3
Recently, Large Language Models (LLMs) have been widely employed in Conversational Recommender Systems (CRSs). Unlike traditional language model approaches that focus on training,…