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Showing papers from ELLIS Institute Tübingen & MPI for Intelligent Systems Show all papers

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NeurIPS 2026ELLIS Institute Tübingen & Nanyang TechnologicalEberhard-Karls-Universität TübinXiamenUC BerkeleyQuantization

AlphaQ: Calibration-Free Bit Allocation for Mixture-of-Experts Quantization

AlphaQ allocates MoE quantization bits without calibration using heavy-tailed spectral analysis, outperforming calibration-based methods and achieving near full-precision accuracy at 3.5-bit average precision.

Wanqi Yang, Yuexiao Ma, Alexander Conzelmann, Xiawu Zheng and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 2 on Hugging Face

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5
76%Highly rated
NeurIPS 2026Technical University of MunichTsinghuaTsinghua Univ, TsinghuaELLIS Institute Tübingen & MLLM reasoning & chain of thought

Learning from the Self-future: On-policy Self-distillation for dLLMs

d-OPSD applies on-policy self-distillation to diffusion LLMs via suffix conditioning and step-level supervision, cutting optimization steps by ~90% versus RLVR while outperforming baselines on reasoning benchmarks.

Yifu Luo, Zeyu Chen, Haoyu Wang, Xinhao Hu and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 174 on Hugging Face · Code ★ 18

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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it
lenient 3/5
medium 7/10
strict 0/5