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Denoising Blocks, Not Tokens: Efficient Compressed Continuous Diffusion with Branching Token Realization
Diffusion language models (DLMs) generate text through iterative parallel refinement, offering the potential for higher throughput than autoregressive (AR) decoding. However, most DLMs still maintain one generative state per token, so every denoising step processes a state sequence as long as the ou
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