AsyncPatch Diffusion introduces asynchronous per-region noise levels in diffusion models, proves a valid ELBO, and uses a controlled sampler to support spatially adaptive generation and native inpainting.
Diffuse everything: Multimodal diffusion models on arbitrary state spaces
6 Pith papers cite this work. Polarity classification is still indexing.
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Generalizes neural transport methods for free energy estimation to any state space with added algebraic and group-theoretic results on time reversal and h-transforms.
LangFlow is the first continuous diffusion language model to rival discrete diffusion on perplexity and generative perplexity while exceeding autoregressive baselines on several zero-shot tasks.
CCDD defines a joint multimodal diffusion on continuous representation space and discrete token space to combine expressivity with explicit token supervision for diffusion language models.
Controlla learns identity and attribute factors from multimodal inputs and aligns them with graph priors using graph-constrained optimal transport to enforce consistent attribute trajectories while preserving reference identity.
Muddit is a unified discrete diffusion transformer that integrates strong visual priors from a pretrained text-to-image model with a lightweight text decoder to enable fast parallel generation across text and image modalities.
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Free energy Estimation on Any State Space
Generalizes neural transport methods for free energy estimation to any state space with added algebraic and group-theoretic results on time reversal and h-transforms.