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A. Tewari

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#machine learning Preprint Sep 2026

Entropy Regularization: A Free Correction to Cross-Entropy for Verified Demonstrations

It is shown that minimizing cross-entropy can be misaligned with minimizing verifier risk; two policies can assign identical likelihood to the observed demonstrations while placing different probability mass on incorrect outputs, and entropy-regularized training consistently improves verifier accuracy over standard cro...

Mihir Dhanakshirur, Adam Ousherovitch, A. Tewari · 0 citations
#artificial intelligence Preprint Sep 2026

Direct Optimization of Generators for Search in Automated Theorem Proving

This work extends Compute-Aligned Training to this setting through an abstraction of policy-guided search, deriving tractable, trace-supported losses and introduces a search-agnostic uniform-allocation (UA) loss that accounts for the budget without specifying the specific search.

Adam Ousherovitch, A. Tewari · 0 citations

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