Unverified50% confidenceFactExact time
A Diffusion Language Model (DLM) first initializes the entire sequence as noise and then restores the text through multiple denoising steps; it can process the whole sequence in parallel and naturally supports scoring over a fixed candidate set.
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10/12/2026
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UnverifiedThe generation pipeline of Diffusion-LM consists of three steps: mapping words to continuous vectors using learnable word embeddings, iteratively denoising via the diffusion model to obtain a sequence of continuous latent variables, and restoring continuous vectors to discrete text through a Rounding operation.79% 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74% 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）74% similarUnverifiedThe Stable Diffusion model consists of three key components: a Variational Autoencoder (VAE), a noise prediction network based on U-Net architecture, and a CLIP-based text encoder.72% similar
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