PA-BDM adapts block diffusion by switching to causal intra-block denoising and dynamically committing reliable prefixes to KV cache, yielding higher accuracy and 71.6% higher throughput than a comparable baseline on document benchmarks.
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Spherical flows on S^{d-1} with vMF noise reduce the continuity equation to a scalar ODE in cosine similarity, yielding posterior-weighted marginal velocity and score that enable ODE and predictor-corrector sampling for categorical sequences, with the posterior trained by cross-entropy and empirical
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Prefix-Adaptive Block Diffusion for Efficient Document Recognition
PA-BDM adapts block diffusion by switching to causal intra-block denoising and dynamically committing reliable prefixes to KV cache, yielding higher accuracy and 71.6% higher throughput than a comparable baseline on document benchmarks.
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Spherical Flows for Sampling Categorical Data
Spherical flows on S^{d-1} with vMF noise reduce the continuity equation to a scalar ODE in cosine similarity, yielding posterior-weighted marginal velocity and score that enable ODE and predictor-corrector sampling for categorical sequences, with the posterior trained by cross-entropy and empirical