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Showing papers from Ohio State University Show all papers

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NeurIPS 2026Ohio State University, ColumbusThe Ohio StateOhio StateAlignment & preference optimization

PORT: Preference Optimization via Robust Token-Level Reweighting

Ding Zhu, Xiukun Wei, Tian Xie, Zhihui Zhu and 2 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026PurdueOhio StateLearning theory

Order-Optimal Sample Complexity for Distribution Learning via Flow Matching

Hari K Sahoo, Mudit G Gaur, Vaneet Aggarwal

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

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57%Worth a look
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NeurIPS 2026The Ohio StateNanjingOhio StateOhio State University, ColumbusMedical imaging

Fourier Contour Learning for Efficient and Traceable Cardiac MRI Quantification

Yi Yu, Zhenyu Bu, Ziyu Zhang, Yixuan Liu and 6 more

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

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NeurIPS 2026Virginia TechAppleU Michigan - Ann ArborVirginia Polytechnic Institute aThe Ohio StateControllable generation

TaxaAdapter: Scaling Fine-grained Species Image Generation To the Tree of Life

Mridul Khurana, Amin Karimi Monsefi, Justin Lee, Medha Sawhney and 8 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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78%Highly rated
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NeurIPS 2026North Carolina StateU Texas at ArlingtonU Alabama, BirminghamUniJohns HopkinsDukeMultimodal reasoning

Leveraging Latent Visual Reasoning in Silence

Latent visual reasoning enhances multimodal training despite being largely unused at inference; attention-based reinforcement learning preserves its benefits by promoting latent-text interaction during training.

Dongyao Zhu, Zhen Wang, Xi Xiao, Han Jiang and 6 more

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

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AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 1/5
71%Highly rated
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NeurIPS 2026PurdueOhio StateRL for LLMs

Oracle-Robust Online Alignment for Large Language Models

Under misspecified preference oracles, online LLM alignment minimizes a worst-case objective that decomposes into loss plus a sensitivity penalty, with projected updates achieving near-optimal complexity.

Zimeng Li, Mudit G Gaur, Vaneet Aggarwal

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

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AI panel: 7 of 20 reviewers recommend it
lenient 2/5
medium 3/10
strict 2/5