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Showing papers from The Ohio State University Show all papers

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NeurIPS 2026The Ohio State University, ColumU MinnesotaThe Ohio StateAutoML & architecture search

Lower-Level Agnostic Bilevel Optimization

Peiwen Qiu, Prashant Khanduri, Jia (Kevin) Liu

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The Ohio StateDeep RL

Finite-Memory Control of POMDPs: Fundamental Limits and Efficient Design

Emrecan Kutay, Atilla Eryilmaz, Ness Shroff

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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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 2026The Ohio StateOhio State University, ColumbusGANs & VAEs

Self-Consuming Generative Models with Co-Evolving Human Preferences

Xiukun Wei, Tian Xie, Ding Zhu, Xueru Zhang

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026The Ohio StateOhio State University, ColumbusGANs & VAEs

Stability and Diversity of Networked Self-Consuming Generative Ecosystems

Xiukun Wei, Yang Zhang, Xueru Zhang

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

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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 2026Georgia Institute of TechnologyThe Ohio StateOhio State University, ColumbusFairness & bias

FedCF: Fair Federated Conformal Prediction

Anutam Srinivasan, Aditya T. Vadlamani, Amin Meghrazi, Srinivasan Parthasarathy

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

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NeurIPS 2026U California, San DiegoIndianaThe Ohio StateUCSDAlignment & preference optimization

Learnable Chernoff Baselines for Provable Inference-Time Alignment

Sunil Madhow, Yuchen Liang, Ness Shroff, Yingbin Liang and 1 more

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

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NeurIPS 2026Ohio State University, ColumbusAlibaba GroupMicrosoft Research AsiaThe Ohio StateEfficient inference & serving

HybridCache: Enhancing Prefix Caching for Linear–Softmax Language Models

Xin Wang, Hao Yu, Yi Zhang, jianwei zhang and 4 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · 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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83%Must read
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NeurIPS 2026The Ohio StateCarnegie MellonOhio State University, ColumbusFeature attribution

Generalized Priority-Aware Shapley Value

GPASV extends priority-aware Shapley values to cyclic weighted priority graphs via penalized violations, yielding differing LLM ensemble valuations.

Kiljae Lee, Ziqi Liu, Weijing Tang, Yuan Zhang

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

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 1/5
88%Must read
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NeurIPS 2026Massachusetts Institute of TechnFacebookThe Ohio StateMetaBytedance Inc.Unified multimodal models

Unifying Contrastive and Generative Objectives for Visual Understanding and Text-to-Image Generation

DREAM unifies contrastive and generative objectives via Masking Warmup, yielding joint visual understanding gains and faster, higher-quality text-to-image generation.

Chao Li, Tianhong Li, Sai V Nuthalapati, Hong-You Chen and 8 more

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

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AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 2/5
80%Must read
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NeurIPS 2026Ohio State University, ColumbusU Pennsylvanianational university of singaore,The Ohio StateTest-time compute

Provable Test-Time Scaling for Beam Search in LLM Reasoning

Modified confidence-filtered beam search achieves near-linear token-level coverage scaling versus quadratic for vanilla beam search, with polynomial horizon dependence that outperforms exponentially scaling Best-of-N methods.

Qijia He, Yu Huang, Yuan Cheng, Yuxin Chen and 1 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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AI panel: 12 of 20 reviewers recommend it
lenient 2/5
medium 8/10
strict 2/5
83%Must read
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NeurIPS 2026The Ohio StateYaleTexas StateOhio State University, ColumbusMolecules & drug discovery

From Retrieval to Reasoning: Agentic Mechanism Prediction from Cell Painting Profiles

PhenoAIR reformulates Cell Painting mechanism prediction as calibrated evidence reasoning via multi-agent evaluation of noisy retrieved neighbors, outperforming matching and LLM baselines across open-world settings.

Jiayuan Chen, Botao Yu, Tianyu Liu, Thai-Hoang Pham and 2 more

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

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5
89%Must read
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NeurIPS 2026The Ohio StateFudanOhio State University, ColumbusAmazonAmazon AGI SFLLM agents & planning

Quest: Training Frontier Deep Research Agents with Fully Synthetic Tasks

QUEST trains open deep research agents via synthetic rubric-tree tasks and context management, achieving frontier-level performance across eight benchmarks with only 8K examples.

Jian Xie, Tianhe Lin, Zilu Wang, Yuting Ning and 15 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 43 on Hugging Face · Code ★ 257

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AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 3/5
78%Highly rated
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NeurIPS 2026The Ohio StateU California, BerkeleyOhio State University, ColumbusUC BerkeleyNeoCognition Ohio StateWeb & GUI agents

Autonomous Continual Learning for Environment Adaptation of Computer-Use Agents

ACuRL enables autonomous continual learning for computer-use agents via curriculum reinforcement learning, yielding 3-29% gains without catastrophic forgetting or human data.

Tianci Xue, Zeyi Liao, Tianneng Shi, Zilu Wang and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5