chess strategy verbalization 1evaluation framework 1human-computer interaction 1large language models 1natural language generation 1
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cs.CL2026
Communicating Chess Strategies in Natural Language
Langyuan Cui, Chun Kai Ling, Hwee Tou Ng
The paper introduces a task for verbalizing chess strategies in natural language, presenting a pipeline to generate such descriptions and an evaluation framework to assess them, de…
cs.CL2026
Enhancing Decision-Making with Large Language Models through Multi-Agent Fictitious Play
Leyang Shen, Yang Zhang, Xiaoyan Zhao +2
Large language model (LLM)-based multi-agent systems (MAS) have demonstrated great potential in solving tasks with execution complexity, by distributing subtasks across cooperative…
cs.CL2026
Game of Thought: Robust Information Seeking with Large Language Models Using Game Theory
Langyuan Cui, Chun Kai Ling, Hwee Tou Ng
Large Language Models (LLMs) are increasingly deployed in real-world scenarios where they may lack sufficient information to complete a given task. In such settings, the ability to…