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S. Ermon

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#natural language process... Preprint Oct 2026

One Block Ahead: Promoting Sampler State in Diffusion Language Models

Block-diffusion language models denoise a whole block of token positions in parallel so each forward pass can emit many tokens. However, blocks are still denoised in strict sequence, a cost that within-block acceleration leaves untouched. Here, we investigate decoding blocks concurrently and propose One Block Ahead (OB...

Yang-Yi Shen, Pin-Jui Ku, Nicolai Oswald et al. · 0 citations

Beyond Pairwise Preferences: Listwise Reward-Aware Alignment for Diffusion Models

Diffusion LAIR is proposed, a reward-aware listwise preference optimization method for diffusion models that outperforms strong preference optimization baselines on SD1.5 and SDXL across text-to-image generation, compositional generation, and image editing benchmarks.

Austin S. Wang, Jiaqi Han, S. Ermon et al. · 1 citation

ABC: Any-Subset Autoregression via Non-Markovian Diffusion Bridges in Continuous Time and Space

This work proposes ABC: Any-Subset Autoregressive Models via Non-Markovian Diffusion Bridges in Continuous Time and Space, and derives SDE dynamics via changes-of-measure on path space, yielding another advantage: path-dependent conditioning on arbitrary subsets of the state history and/or future.

Gabriel Guo, Thanawat Sornwanee, L. Hao et al. · 0 citations

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