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NeurIPS 2026Max Planck Institute of BiochemiMax Planck Institute for BiochemHKUST-GZETH ZurichLudwig-Maximilians-Universität MProteins

Joint protein, mRNA, DNA sequence design and optimization with nucleotide-level Potts models

Blazej Banaszewski, Lars J Dornfeld, Dexiong Chen, Karsten Borgwardt and 1 more

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

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NeurIPS 2026Max Planck Institute of BiochemiDepartment of Machine Learning aMPI of BiochemistryHKUST-GZETH ZurichVision backbones

Channel Mixer: A Pretrainable Tokenizer for Scalable Multi-Channel Vision Transformers

Lukas Miklautz, Lucas Miranda, Nikola Bulat, Armin Lambacher and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The Hong Kong University of ScieThe Hong Kong University of ScieHKUST-GZThe Chinese University of Hong KVision-language-action models

Dodge-It: Learning Collision-Aware VLA Models for Robotic Manipulation

Jiawei Feng, Chuzhao Huang, Xinli Xu, Yingcong Chen

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The Hong Kong University of ScieThe Hong Kong University of ScieGuangzhou Medicalcritical care medicine, GuangzhoHKUST-GZUncertainty & calibration

Robust Conditional Conformal Prediction via Branched Normalizing Flow

Branched Normalizing Flow bounds conditional invalidity via Wasserstein distance and improves robust conditional coverage under distribution shift.

Rui Xu, Xingyuan Chen, Wenxing Huang, Minxuan Huang and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 12 of 20 reviewers recommend it
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NeurIPS 2026The Hong Kong University of ScieJilinHKUST-GZHong Kong University of Science Hallucination & factuality

Geometry-Calibrated Conformal Abstention for Language Models

Conformal Abstention uses geometry-calibrated confidence to decide abstention with finite-sample correctness guarantees, achieving 75% conditional correctness.

Rui Xu, Yi Chen, Sihong Xie, Hui Xiong

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

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AI panel: 11 of 20 reviewers recommend it
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