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Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? 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Proof of the Most Informative Boolean Function Conjecture
Mustafa Kesal · 2015-11-06 · via cs.IT updates on arXiv.org

Suppose $\XX{N}$ is a uniformly distributed $N$-dimensional binary vector and $\YY{N}$ is obtained by passing $\XX{N}$ through a binary symmetric channel with crossover probability $α$. Recently, Courtade and Kumar postulates that $I(f(\XX{N});\YY{N})\leq 1-\Be(α)$ for any Boolean function $f$ \cite{courtade}. In this paper, we provide a proof of the correctness of this conjecture.

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