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Showing papers from University of Michigan Show all papers

91%Must read
arXivRutgers, The State University ofU California San DiegoU MichiganMcGillKing Fahd University of PetroleuLLM agents & planning

False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents

Self-evolving search agents suffer co-cheating where proposers and solvers mutually reinforce errors; CrossFit partitions sources to cross-fit agreement and cuts false agreement by over half, boosting downstream search by 8+ points.

Meijia Chen, Hao Li, Zheng Lu, Hongshan Lin and 11 more

Published Sep 30, 2026 · 0 citations · ▲ 670 on Hugging Face

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strict 3/5
80%Must read
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arXivU Illinois Urbana-ChampaignU MichiganNvidiaNvidiaAI oversight & deception

Covert Assistance: Helpful LLM Agents Evade Oversight in Multi-Agent Systems

Benign multi-agent LLM planners disguise secrets to help developers evade oversight, with rare per-episode leaks compounding to high breach risk across repeated exchanges.

Deema Alnuhait, Gengyu Wang, Muhammad Khalifa, Hao Peng

Published Sep 30, 2026 · 0 citations · ▲ 13 on Hugging Face

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
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NeurIPS 2026U MichiganU Michigan - Ann ArborU Michigan Google ResearchRL for LLMs

VSPO: Vector-Steered Policy Optimization for Controllable Model Behavior

Xuechen Zhang, Zijian Huang, Kai Yang, Weijia Zhang and 2 more

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

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NeurIPS 2026Alibaba Token Hub, Alibaba GroupAlibaba GroupAlibabaDept. of Computer Sci. & EngU MichiganVision-language models

Despa: Resolving Spatial Collapse in VLMs via Depth-Grounded Geometry

Yujing Lou, Pingyi Chen, Shen Cao, Lubin Fan and 3 more

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

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NeurIPS 2026U MichiganU Michigan - Ann ArborVanderbilt University Medical CeAdversarial robustness

A low-rank decoder bottleneck bounds reliability in foundation-model perturbation prediction

Zheyu Zhang, Yuanhao Huang, Fan Feng, Jie Liu

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026U MichiganBayesian & probabilistic methods

Cross-Fitting for Neural Posterior Estimation

Jeffrey Regier

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

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NeurIPS 2026U MichiganMassachusetts Institute of TechnMassachusetts Institute of TechnDeep learning theory

Topological Invariance and Breakdown in Learning Dynamics

Yongyi Yang, Tomaso Poggio, Isaac Chuang, Liu Ziyin

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

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NeurIPS 2026UC RiversideTsinghuaU California, RiversideGoogleGeorgia Institute of TechnologyRobot manipulation

LIBERO-PeRM: Benchmarking Personalized Robotic Manipulation

Zhixu Li, Keqian Tang, Litian Gong, Jingyu Yao and 6 more

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

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NeurIPS 2026U MichiganGuide LabsPrescient Design / GenentechNYUPrescient Design, GenentechRL for LLMs

Are Easier or Harder Examples Better? Rethinking Data Selection for Reward Models and Preference Optimization

Kevin Christian Wibisono, Aya Ismail, Pedro O. Pinheiro, Yixin Wang and 3 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Southern CaliforniaU ArizonaGeneral MotorsU MichiganEmbodied agents

Say the Same, Act Differently: Text-Orthogonal Action Subspaces in Reasoning Vision-Language-Action Models

Zihao Feng, Qingzhao Zhang, Chunyu Xia, Bo Yu and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026KAISTU MichiganKorea Advanced Institute of ScieOffline RL

Offline Constrained Reinforcement Learning under Partial Data Coverage

Seokmin Ko, Ambuj Tewari, Kihyuk Hong

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

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57%Worth a look
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NeurIPS 2026U MichiganU Michigan - Ann ArborThe University of MichiganMichigan StateDiffusion models

Improving Conditional Modeling via Inter-Class Likelihood-Ratio Maximization and Unifying Classifier-Free Guidance with Alignment Objectives

Xiang Li, Yixuan Jia, Xiao Li, Jeffrey Fessler and 2 more

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

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NeurIPS 2026U Michigan - Ann ArborU MichiganLearning theory

Can Ideologues Agree on Quality? From Non-identifiable Latent Factors to Collective Outcomes

David Gamba, Seura Ha, Daniel Romero, Grant Schoenebeck

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

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69%Highly rated
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NeurIPS 2026U Michigan - Ann ArborPrincetonU MichiganAdversarial robustness

BodyBench: Evaluating Adversarial Image Defenses Against AI Nudification Inpainting

Li Qiwei, Salma Abdel Magid, Olga Russakovsky, Eric Gilbert 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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AI panel: 3 of 20 reviewers recommend it
lenient 2/5
medium 1/10
strict 0/5
45%Niche pick
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NeurIPS 2026U MichiganMedical College of WisconsinU Michigan - Ann ArborClinical NLP & EHR

NNCoxKL: Risk-Set Distillation from Probability-Free Prognostic Teachers for Deep Cox Models

Lingfeng Luo, Jeremy M Taylor, Di Wang, Feiyang Deng and 2 more

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

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NeurIPS 2026Carnegie MellonU Michigan - Ann ArborU MichiganModel OSStanfordLLM pretraining & scaling laws

Witness Overlap: Directional Provenance Inside Open-Weight Model Families

Siyuan Li, Haoxuan Zeng, Xin Luo, Fernando Jia and 5 more

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

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76%Highly rated
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NeurIPS 2026BCAMBasque Center for Applied MathemU MichiganLearning theory

Estimation of the Label-Noise Transition Matrix with Performance Guarantees via Selective Classification

A selective-classification method estimates label-noise transition matrices with finite-sample guarantees while bypassing fragile class-posterior estimation.

Xabier de Juan, Santiago Mazuelas, Yilun Zhu, Clay Scott

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

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AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 0/5
80%Must read
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NeurIPS 2026U MichiganMichigan StateDomain adaptation

Language-Induced Priors for Domain Adaptation

Using expert text descriptions to build LLM-derived priors guides domain selection under scarce target data, yielding near-oracle cold-start error and asymptotic consistency.

Qiyuan Chen, Jiayu Zhou, Raed AL Kontar

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

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
72%Highly rated
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NeurIPS 2026U MichiganThe Chinese University of Hong KTest-time compute

Confidence-Based Decoding is Provably Efficient for Diffusion Language Models

Confidence-based decoding achieves ε-accurate diffusion language model sampling in Õ(H(X₀)/ε) iterations by adaptively unmasking tokens until cumulative entropy exceeds a threshold.

Changxiao Cai, Gen Li

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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AI panel: 8 of 20 reviewers recommend it
lenient 4/5
medium 3/10
strict 1/5
78%Highly rated
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NeurIPS 2026NorthwesternNorthwestern University, NorthweU MichiganDiffusion models

DiffATS: Diffusion in Aligned Tensor Space

DiffATS uses orthogonal Procrustes-aligned Tucker primitives to enable direct diffusion modeling of high-resolution spatiotemporal fields, achieving 3.9x to 210x compression without pretrained autoencoders.

Jinhua Lyu, Tianmin Yu, Brian Kim, Lizhuo Zhou and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · 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 4/5
medium 5/10
strict 2/5
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