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Sara Hooker - Why US AI Act Compute Thresholds Are Misguided

Machine Learning Street Talk (MLST)

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Advancements in RLHF for Multilingual Models

This chapter explores the intricacies of Reinforcement Learning from Human Feedback (RLHF) and critiques traditional methods like Proximal Policy Optimization in language processing. It discusses innovative approaches and the challenges of multilingual training, particularly addressing issues related to translation and the concept of translationese.

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