Accelerating Diffusion LLMs via Adaptive Parallel Decoding

arXiv — cs.LG•Monday, November 3, 2025 at 5:00:00 AM

A new method called adaptive parallel decoding (APD) has been introduced to enhance the speed of diffusion large language models (dLLMs) without compromising quality. Traditionally, the generation speed of language models has been limited by autoregressive decoding, which predicts tokens one at a time. APD allows for parallel token generation, potentially revolutionizing how quickly and efficiently these models can operate. This advancement is significant as it could lead to faster and more effective applications of AI in various fields, making technology more accessible and efficient.

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