Full text: a residual on Maia-3 logits with Stockfish features improves chess move prediction and yields a 32-d style embedding that is weakly Elo-predictive; the abstract's Matilda/Go claims are absent.
arXiv preprint arXiv:2409.12272 , year=
2 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
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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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Matilda: Engine-Agnostic Search with Human Policy Guidance
Full text: a residual on Maia-3 logits with Stockfish features improves chess move prediction and yields a 32-d style embedding that is weakly Elo-predictive; the abstract's Matilda/Go claims are absent.
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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.