CREST. CREST is a training-free test-time steering framework that discovers cognitive heads via simple offline calibration and then rotates activations during decoding to guide the model’s reasoning—preserving norms to avoid per-model hyperparameter tuning. This improves accuracy and reduces tokens across models and datasets.

Problem

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Audience

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Market

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Pricing

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.