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NeurIPS 2026New YorkNewYorkInstitute of Computing TechnologNous ResearchModalTest-time compute

Multi-Token Residual Prediction

Multi-token Residual Prediction predicts next-step residuals via hidden states to denoise more tokens per pass, accelerating diffusion language models up to 1.4x or recovering up to 22.6 accuracy points on HumanEval.

Yufeng Xu, Zishuo Bao, Qian Wang, Zeshen Zhang and 5 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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16/20 AI panelreviewers recommend it

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AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 1/5
80%Must read
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NeurIPS 2026Nous ResearchEfficient & distributed training

Efficient Pre-Training with Token Superposition

Token-Superposition Training combines contiguous tokens into multi-hot bags to boost pre-training throughput, cutting 10B-scale pre-training time up to 2.5x at equal loss.

Bowen Peng, Théo Gigant, Jeffrey Quesnelle

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 2/5