Unverified50% confidenceFactExact time
During MDM generation, the conditional distribution at each position can be computed simultaneously, which naturally supports parallel decoding, in sharp contrast to the way autoregressive models generate tokens one by one.
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10/16/2026
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UnverifiedUnlike autoregressive models that strictly generate from left to right, MDLMs theoretically allow parallel filling of arbitrary positions.73% similarUnverifiedThe noising process of a masked diffusion model (MDM) progressively replaces tokens in the sequence with a special [MASK] token, and the training objective is for the model to learn to predict the original token at each masked position based on the currently partially visible sequence.72% similarUnverifiedLLM模型在「生成」和「评估」时所激活的推理路径不同，同一模型生成代码时可能忽略某个边界条件，但在评估另一份代码时却能识别该问题69% similarUnverifiedLLM的每次调用可以被建模为伯努利试验，N次独立调用的通过次数服从二项分布B(N, p)68% similarUnverifiedThe paper assumes access to a generative model of the MDP, meaning the algorithm can query samples for any state-action pair.68% similar
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