ALoDLM: Adaptively Looped Diffusion Language Models
Diffusion language models (DLMs) enable fast generation by predicting multiple tokens in parallel, but their practical adoption remains limited by a persistent quality gap relative to comparably sized autoregressive (AR) models. We attribute this gap to a computation-difficulty mismatch: within a partially observed seq...
Lian-Cheng Fang, Zhuo-Wei Li, Youngeun Kim et al.
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