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Dystruct: Dynamically Structured Diffusion Language Model Decoding via Bayesian Inference
Diffusion language models (DLMs) have recently emerged as a promising alternative to autoregressive models, primarily due to their ability to enable parallel decoding. Despite this advantage, most existing DLMs rely on a fixed generation length specified prior to decoding, which restricts their flex
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