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Showing papers from State University of New York, Stony Brook Show all papers

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NeurIPS 2026SUNY - University at Stony BrookU North Carolina at CharlotteStony BrookState University of New York at State University of New York, StMedical imaging

Anatomy-Preserving Unpaired Medical Image Translation via Shared Latent Anchoring

Zhilin Zou, Hieu Le, Saumya Gupta, Jingyi Xu and 2 more

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

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NeurIPS 2026State University of New York at Stony BrookArgonne National LaboratoryAcademic medical center at StateU UtahDiffusion models

BigCell: Generating Gigapixel Whole-Slide Images

Srikar Yellapragada, Alexandros Graikos, Zilinghan Li, Kostas Triaridis and 9 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026TempleState University of New York, StFederated learning

A Doubly Smoothed Decentralized Stochastic Minimax Optimization Algorithm

Xinwen Zhang, Chiu C Tan, Haibin Ling, Hongchang Gao

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Stony BrookETS MontrealState University of New York, StAutoregressive generation

Unlocking Any-Order Generation in Pretrained Autoregressive Image Models

Rishav Pramanik, Marco Pedersoli, Zhaozheng Yin

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Stony BrookRowan2nd Set AIPrelight IncState University of New York, StText-to-image

SANEval: Open-Vocabulary Compositional Benchmarks with Failure-mode Diagnosis

SANEval introduces open-vocabulary compositional benchmarks using LLM-based prompt understanding and open-vocabulary detection to diagnose text-to-image failure modes. Its automated metric correlates more faithfully with human judgments across attribute binding, spatial relations, and numeracy than

Rishav Pramanik, Ian Nielsen, Jeffrey Smith, Saurav Pandit and 2 more

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

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5