Language Models that Play Chess and Explain Their Moves
Modern chess engines are silent experts: they play at a superhuman level, but do not offer explanations for their play. On the other hand, language models (LMs) can generate plausible-sounding explanations, but their weak playing strength limits the utility of their explanations. We introduce Queen, a 4B-parameter chess-language model that can explain its moves and plans while
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Modern chess engines are silent experts: they play at a superhuman level, but do not offer explanations for their play. On the other hand, language models (LMs) can generate plausible-sounding explanations, but their weak playing strength limits the utility of their explanations. We introduce Queen, a 4B-parameter chess-language model that can explain its moves and plans while
This paper demonstrates a significant step towards creating explainable AI systems by integrating expert domain knowledge with language models. For ML engineers, understanding how to combine silent expert systems with LMs to generate coherent and accurate explanations is crucial for developing more transparent and trustworthy AI applications across various domains.