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A single objective directly optimizes speculative decoding efficiency, eliminating auxiliary hyperparameters and achieving state-of-the-art performance across multiple tasks.
Diffusion language models can now adapt to the underlying data structure without hyperparameter tuning, thanks to a new randomized unmasking schedule that provably accelerates sampling.