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Hierarchical Continuous Diffusion Language Models

Hui Ren, Zihan Li, Chang Liu, Huidong Liu, Alexander Schwing

Keeps a continuous state throughout denoising while reading out tokens at each step and feeding them back into the next state update. Tests whether this coupling preserves dependencies during parallel generation on Sudoku, Countdown, and language modeling.

First public: · Added to this list: October 18, 2026

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arXiv:2610.02193 · Initial submission: 2026-10-01

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Continuous-state reasoning — Use vectors—lists of numbers—to carry intermediate reasoning from one step to the next, instead of selecting a text token at every step. Some methods use the model's hidden states; others combine several candidate token representations.

Alternative generation methods — Change how intermediate steps are generated, revised, or searched—for example, by refining several steps in parallel. These are related approaches: some still produce written chains of thought.

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