LIMO achieves 63.3% on AIME24 and 95.6% on MATH500 via supervised fine-tuning on roughly 1% of the data used by prior models, supporting the claim that minimal strategic examples suffice when pre-training has already encoded domain knowledge.
arXiv preprint arXiv:2402.04494 , year=
4 Pith papers cite this work, alongside 8 external citations. Polarity classification is still indexing.
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UNVERDICTED 4representative citing papers
The paper identifies four missing interfaces (data autolabelling, embodiment retargeting, physics-grounded world models, and video-based reward inference) as the central bottleneck beyond VLA scaling for robot intelligence.
Per-100-Elo-band transformers outperform Maia-2 in move prediction accuracy across all bands and reach 0.78 AUC on outcome prediction using held-out Lichess data.
A CNN autoencoder that encodes the entire chessboard state improves MLP prediction of relative piece values by 16% MAE reduction to roughly 0.65 pawns using 12 million Stockfish-labeled positions from grandmaster games.
citing papers explorer
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LIMO: Less is More for Reasoning
LIMO achieves 63.3% on AIME24 and 95.6% on MATH500 via supervised fine-tuning on roughly 1% of the data used by prior models, supporting the claim that minimal strategic examples suffice when pre-training has already encoded domain knowledge.
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Robots Need More than VLA and World Models
The paper identifies four missing interfaces (data autolabelling, embodiment retargeting, physics-grounded world models, and video-based reward inference) as the central bottleneck beyond VLA scaling for robot intelligence.
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ChessMimic: Per-Rating Transformer Models for Human Move, Clock, and Outcome Prediction in Online Blitz Chess
Per-100-Elo-band transformers outperform Maia-2 in move prediction accuracy across all bands and reach 0.78 AUC on outcome prediction using held-out Lichess data.
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PAWN: Piece Value Analysis with Neural Networks
A CNN autoencoder that encodes the entire chessboard state improves MLP prediction of relative piece values by 16% MAE reduction to roughly 0.65 pawns using 12 million Stockfish-labeled positions from grandmaster games.