用自然语言解释国际象棋策略，让人类和大模型都看得懂。
Communicating Chess Strategies in Natural Language
- 构建策略描述流水线，将棋局思路转为自然语言
- 实验证明语言描述能有效传递战略信息
- 适合想理解棋局思路的棋手和研究可解释性的人
国际象棋引擎已具备超人类水平的棋力，但其走法背后的策略对人类玩家（包括高手）而言仍难以理解。为此，我们提出国际象棋策略语义化任务，旨在用自然语言描述棋局策略。我们设计了（i）一套策略描述生成流水线，以及（ii）一个客观评估生成描述质量的框架。实验表明，自然语言是向人类和大语言模型传递战略信息的一种有前景且可解释的媒介。此外，我们获得若干新见解：（a）评估应超越主线路；（b）纯概念描述存在局限；（c）依赖大模型而非人类进行评估存在不足。
原文摘要 · Abstract (English)
Chess engines have long achieved superhuman playing strength. However, the underlying strategy behind their move suggestions is difficult for human players, even skilled ones, to comprehend. Motivated by this, we propose the task of chess strategy verbalization, which is to describe chess strategies in natural language. We design (i) a pipeline for verbalizing strategies and (ii) an evaluation framework for objective evaluation of generated strategy descriptions. Our experiments show that natural language is a promising and interpretable medium for communicating strategic information to both human and LLM players. We glean additional interesting insights, including (a) the importance of evaluating strategies beyond the main line, (b) the limitations of pure concept-based descriptions, and (c) the limitations of relying on LLMs rather than humans for evaluation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。