Unverified50% confidenceFactExact time
Representative discrete diffusion works include the Masked Diffusion Language Model (MDLM) and its subsequent improvements, and have been applied to the generation of structured data such as code and protein sequences.
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50%
Confidence
Medium-term (~90 days)
Relevance
10/2/2026
First Seen
Valid until: 12/31/2026
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UnverifiedDiscrete diffusion models specifically handle discrete data (such as amino acid sequences, DNA sequences, or text); the forward process typically employs a masking mechanism that replaces certain positions in the sequence with [MASK] tokens, which the model progressively predicts and restores during the reverse process.73% similarUnverifiedDiffusion-LM is widely recognized as the pioneering work in the direction of diffusion language models.72% similarUnverified离散扩散语言模型主流方案包括：将token映射到连续嵌入空间进行扩散（如Diffusion-LM），或设计离散扩散过程用掩码模拟加噪（如D3PM、MDLM）71% similarVerified扩散模型是一类基于马尔可夫链的生成模型，核心思想是通过前向加噪和反向去噪来捕捉数据分布70% similarUnverifiedDiscrete diffusion models construct complete sequences by iteratively and in parallel resolving multiple tokens across multiple steps, unlike the left-to-right word-by-word generation of autoregressive models.70% similar
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