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ChessMimic models predict human chess moves and outcomes

Researchers have developed ChessMimic, a system employing three specialized transformer models to predict human chess moves, thinking times, and game outcomes in online blitz games. Each model is trained for specific Elo rating bands to improve accuracy across different skill levels. The move prediction model surpasses existing benchmarks like Maia-2, while the outcome model achieves a 0.78 AUC, outperforming simpler logistic regressions. Although the thinking time prediction model is not state-of-the-art, it provides a usable signal for analysis. AI

IMPACT Introduces specialized models for predicting human chess performance, potentially aiding AI training and analysis.

RANK_REASON The cluster contains a research paper detailing a new AI model for chess prediction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Thomas Johnson ·

    ChessMimic: Per-Rating Transformer Models for Human Move, Clock, and Outcome Prediction in Online Blitz Chess

    arXiv:2606.04473v1 Announce Type: cross Abstract: We present ChessMimic, a system of three small encoder-only transformers - for move, thinking-time, and outcome prediction - conditioned on the position, recent move history, player rating, and clock state. We fit a separate insta…