Guided research walkthrough · about 6 minutes

MoveLens

Statistical evidence, language-model preference, and human move modeling — evaluated on the same chess positions. Everything here is precomputed research output served as static files; no backend is needed.

Can language-model move preferences add signal beyond chess statistics?

The same chess position is evaluated three ways, then the signals are combined to ask whether the combination predicts more than any one alone.

Regan-inspiredStatistical model (public reconstruction)

What looks unusual statistically?

Input
Player rating, Stockfish MultiPV lines (depth 12), position difficulty.
Output
Projected chance of matching the engine's first / top-3 move; z-score of the observed match rate. No probability per legal move.
Role
Statistical baseline: what looks unusual relative to the expected rate for this rating?
Strength
Transparent, every quantity inspectable; highest ROC-AUC of the single scores evaluated so far on the controlled-substitution benchmark (Qwen not yet evaluated; substitutes are engine lines by construction, which favours engine-match statistics).
Limitation
Not Professor Regan's analyzer. Cannot rank or score individual moves, so it cannot be compared move-by-move.
Qwen3-8B-BaseGeneral-purpose LLM
Implemented and tested · scoring run pending

What does a general-purpose language model prefer?

Input
A fixed text prompt: ratings, side to move, FEN, all legal moves and Stockfish lines. The played move is never marked.
Output
Each legal move's summed token log-likelihood, softmax-normalized into a distribution over the legal moves.
Role
General-purpose language-model preference over candidate moves, evaluated for predictive value.
Strength
No chess-specific training objective: tests what a general LLM already encodes.
Limitation
Held-out run pending: no held-out Qwen score exists. General language model; likelihoods depend on tokenization and move notation.
Maia-3 79MChess-specific human-move transformer

What would a human of this rating tend to play?

Input
Board (plus recent positions) and both players' ratings.
Output
A probability for every legal move, conditioned on rating.
Role
Human move model: what would a player of about this strength tend to play?
Strength
A full human-move distribution; on the engine-first-move event it beats the reconstruction (paired bootstrap). Separates engine-optimal from human-plausible moves.
Limitation
Models human move preference, not cheating. A chess-specific transformer (Chessformer), not a language model.
Qwen evaluation pending. 0 of 12,863 held-out test positions have been scored by Qwen3-8B-Base. The scorer, frozen prompt and evaluation code are implemented and tested; no Qwen result is shown or estimated.

This is an independent reconstruction based on publicly documented concepts and is not Professor Regan's production analyzer.

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