Distilling Stockfish value function into ResNet and ViT models

A new project distills the Stockfish value function into ResNet and ViT architectures using a 3.9B position dataset derived from Lichess games. Findings suggest CNNs outperform ViTs in early training stages due to superior geometric inductive biases for board representation.