Showing cs.CLShow all
3 papers · 1 filter
cs.CL2025
GroupDebate: Enhancing the Efficiency of Multi-Agent Debate Using Group Discussion
Tongxuan Liu, Xingyu Wang, Weizhe Huang +5
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse NLP tasks. Extensive research has explored how to enhance the logical reasoni…
cs.CL2025
S-MAD: Breaking the Token Barrier to Enhance Multi-Agent Debate Efficiency
Yuting Zeng, Weizhe Huang, Lei Jiang +5
Large language models (LLMs) have demonstrated remarkable capabilities across various natural language processing (NLP) scenarios, but they still face challenges when handling comp…
cs.CL2025
Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models
Tongxuan Liu, Wenjiang Xu, Weizhe Huang +5
Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks but their performance in complex logical reasoning tasks remains unsatisfactory. Althoug…