Tempered remasking heuristics increase diversity in diffusion language model sampling, closing the pass@k gap with autoregressive methods at equivalent computational cost.
2.Revealing anchors linearly degrades the fork entropy: Hqℓ θ (xℓ 0 |x t′ ) =H qℓ θ (xℓ 0 |x t)− ∑ a∈A\M t′ ηa (7) where Hqℓ θ (xℓ 0 |x t)> ∑a∈A ηa >0
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A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models
Tempered remasking heuristics increase diversity in diffusion language model sampling, closing the pass@k gap with autoregressive methods at equivalent computational cost.