杜雪峰｜沈阳理工大学｜学者主页

2026

Teach AI What It Doesn't Know

Xuefeng Du

AAAI Conference on Artificial Intelligence

2026

Towards Reducible Uncertainty Modeling for Reliable Large Language Model Agents

Changdae Oh, Seongheon Park, To Eun Kim, Jia-Tong Li, Wendi Li, Samuel Yeh, Xuefeng Du, Hamed Hassani, P. Bogdan, D. Song, Sharon Li

arXiv.org

DOI

2026

VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation

Seongheon Park, Changdae Oh, Hyeong Kyu Choi, Xuefeng Du, Sharon Li

Annual Meeting of the Association for Computational Linguistics

DOI

2026

Improving Neural Architecture Search by Minimizing Worst-Case Validation Loss

Haochen Zhang, Xuefeng Du, Ruisi Zhang, Peng-Tao Xie

IEEE Transactions on Artificial Intelligence

DOI

2026

Unlocking the Pre-Trained Model as a Dual-Alignment Calibrator for Post-Trained LLMs

Bei-Er Luo, Cheng Wang, Hongxin Wei, Sharon Li, Xuefeng Du

arXiv.org

DOI

2026

Harnessing Reasoning Trajectories for Hallucination Detection via Answer-agreement Representation Shaping

Jian-Xiong Zhang, Bing Guo, Yu-Ming Jiang, Hao-Bo Wang, Bo An, Xuefeng Du

arXiv.org

DOI

2025

Identification of Peanut Cultivars with Low Cadmium Contents and Their Rhizosphere Microbial Characteristics in Alkaline and Acidic Cadmium-Contaminated Fields

Ke Zhang, Xuefeng Du, Xiaoli Li, Shuangshuang Li, Hui Liu, Liyong Bai, Jiulan Dai

Sustainability，Vol. 17, No. 2

DOI

2025

Foundations of Unknown-aware Machine Learning

Xuefeng Du

arXiv.org

DOI

2025

Steer LLM Latents for Hallucination Detection

Seongheon Park, Xuefeng Du, Min-Hsuan Yeh, Hao-Bo Wang, Yixuan Li

International Conference on Machine Learning

2025

Exploring transition states of protein conformational changes via out-of-distribution detection in the hyperspherical latent space

Bo-Jun Liu, Jordan G Boysen, I. Unarta, Xuefeng Du, Yixuan Li, Xu-Hui Huang

Nature Communications

DOI

2025

Position: Challenges and Future Directions of Data-Centric AI Alignment

Min-Hsuan Yeh, Jeffrey Wang, Xuefeng Du, Seongheon Park, Leitian Tao, S. Im, Yixuan Li

International Conference on Machine Learning

2025

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

Changdae Oh, Zhen Fang, S. Im, Xuefeng Du, Yi-Xuan Li

International Conference on Machine Learning

DOI

2025

Limited Preference Data? Learning Better Reward Model with Latent Space Synthesis

Leitian Tao, Xuefeng Du, Yixuan Li

Neural Information Processing Systems

DOI

2024

Out-of-Distribution Learning with Human Feedback

Hao-Yue Bai, Xuefeng Du, Katie Rainey, Shibin Parameswaran, Yixuan Li

Trans. Mach. Learn. Res.

DOI

2024

Safety-Aware Fine-Tuning of Large Language Models

Hyeong Kyu Choi, Xuefeng Du, Yixuan Li

arXiv.org

DOI

2024

HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection

Xuefeng Du, Chaowei Xiao, Yixuan Li

Neural Information Processing Systems

DOI

2024

When and How Does In-Distribution Label Help Out-of-Distribution Detection?

Xuefeng Du, Yiyou Sun, Yixuan Li

International Conference on Machine Learning

DOI

2024

How Does Unlabeled Data Provably Help Out-of-Distribution Detection?

Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li

International Conference on Learning Representations

DOI

2023

Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection

Hao-Yue Bai, Gregory H. Canal, Xuefeng Du, Jeongyeol Kwon, R. Nowak, Yi-Xuan Li

International Conference on Machine Learning

DOI

2023

Non-Parametric Outlier Synthesis

Leitian Tao, Xuefeng Du, Xiao-Jin Zhu, Yi-Xuan Li

International Conference on Learning Representations

DOI

2023

OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection

Jingyang Zhang, Jingkang Yang, Pengyun Wang, Haoqi Wang, Yueqian Lin, H. Zhang, Yiyou Sun, Xuefeng Du, Kai-Yang Zhou, Wayne Zhang, Yi-Xuan Li, Zi-Wei Liu, Yi-Ran Chen, H. Li

J. Data-centric Mach. Learn. Res.

DOI

2023

Dream the Impossible: Outlier Imagination with Diffusion Models

Xuefeng Du, Yiyou Sun, Xiao-Jin Zhu, Yi-Xuan Li

Neural Information Processing Systems

DOI

2022

Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild

Xuefeng Du, Xin Wang, Gabriel Gozum, Yi-Xuan Li

Computer Vision and Pattern Recognition

DOI

2022

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection

Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kun Ding, Wen-Hsiao Peng, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, Xuefeng Du, Kai-Yang Zhou, Wayne Zhang, Dan Hendrycks, Yi-Xuan Li, Zi-Wei Liu

Neural Information Processing Systems

DOI

2022

SIREN: Shaping Representations for Detecting Out-of-Distribution Objects

Xuefeng Du, Gabriel Gozum, Yifei Ming, Yi-Xuan Li

Neural Information Processing Systems

DOI

2022

VOS: Learning What You Don't Know by Virtual Outlier Synthesis

Xuefeng Du, Zhaoning Wang, Mu Cai, Yi-Xuan Li

International Conference on Learning Representations

2021

矿井主通风机监测和健康状态评估方法与系统研究

杜雪峰

《西安科技大学》

2021

煤矿主要通风机风量传感器布置方法研究

李曼，杜雪峰，曹现刚，霍曼，马欢

《煤矿安全》

2021

PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels

Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tong-Liang Liu, Tingyang Xu, Wen-Bing Huang, Jun-Zhou Huang

arXiv.org

2021

Learning Diverse-Structured Networks for Adversarial Robustness

Xuefeng Du, Jing-Feng Zhang, Bo Han, Tong-Liang Liu, Yu Rong, Gang Niu, Jun-Zhou Huang, Masashi Sugiyama

International Conference on Machine Learning

2021

Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions

Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tong-Liang Liu, Tingyang Xu, Wen-Bing Huang, Yi-Xuan Li, Jun-Zhou Huang

Trans. Mach. Learn. Res.

2021

How to Save your Annotation Cost for Panoptic Segmentation?

Xuefeng Du, Chenhan Jiang, Hang Xu, Geng-Wei Zhang, Zhen-Guo Li

AAAI Conference on Artificial Intelligence

DOI

2021

Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography

Xuefeng Du, Haohan Wang, Zhen-Xi Zhu, Xiangrui Zeng, Yi-Wei Chang, Jing Zhang, E. Xing, Min Xu

Bioinform.

DOI

2020

矿用本安直流电源自动测试系统

李曼，王启亮，段雍，杜雪峰

《现代电子技术》

2020

无底柱分段崩落法在地下铁矿中的应用

杜雪峰

《价值工程》

DOI

2020

地下矿山工程井巷掘进爆破技术探讨

杜雪峰

《世界有色金属》

2020

Skillearn: Machine Learning Inspired by Humans' Learning Skills

Peng-Tao Xie, Xuefeng Du, Hao Ban

arXiv.org

DOI

2020

Learning by Passing Tests, with Application to Neural Architecture Search

Xuefeng Du, Hao-Chen Zhang, Peng-Tao Xie

arXiv.org

DOI

2020

Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding

Lin Lan, P. Wang, Xuefeng Du, Kaikai Song, Jing Tao, X. Guan

Neural Information Processing Systems

2020

Small-Group Learning, with Application to Neural Architecture Search

Xuefeng Du, Peng-Tao Xie

arXiv.org

2019

Classification in Cryo-Electron Tomograms

I. Gubins, Gijs van der Schot, R. Veltkamp, F. Förster, Xuefeng Du, Xiangrui Zeng, Zhen-Xi Zhu, Lufan Chang, Min Xu, E. Moebel, A. Martínez-Sánchez, Charles Kervrann, T. Lai, Xusi Han, Genki Terashi, D. Kihara, Benjamin A. Himes, Xiao-Hua Wan, Jingrong Zhang, Shan Gao, Yu Hao, Zhilong Lv, Zhidong Yang, Zijun Ding, Xuefeng Cui, Fa Zhang

3DOR@Eurographics

DOI

2019

Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss

Xuefeng Du, Xiangrui Zeng, Bo Zhou, Alex Singh, Min Xu

British Machine Vision Conference

2019

Semi-supervised Macromolecule Structural Classification in Cellular Electron Cryo-Tomograms using 3D Autoencoding Classifier

Siyuan Liu, Xuefeng Du, Rong Xi, Fuya Xu, Xiangrui Zeng, Bo Zhou, Min Xu

British Machine Vision Conference

RISING STARS IN DATA SCIENCE

Raul Astudillo, Valerie Chen, Uthsav Chitra, Xuefeng Du, Hans W. A. Hanley, Keegan Harris

精选作品

期刊论文

Teach AI What It Doesn't Know

Towards Reducible Uncertainty Modeling for Reliable Large Language Model Agents

VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation

Improving Neural Architecture Search by Minimizing Worst-Case Validation Loss

Unlocking the Pre-Trained Model as a Dual-Alignment Calibrator for Post-Trained LLMs

Harnessing Reasoning Trajectories for Hallucination Detection via Answer-agreement Representation Shaping

Identification of Peanut Cultivars with Low Cadmium Contents and Their Rhizosphere Microbial Characteristics in Alkaline and Acidic Cadmium-Contaminated Fields

Foundations of Unknown-aware Machine Learning

Steer LLM Latents for Hallucination Detection

Exploring transition states of protein conformational changes via out-of-distribution detection in the hyperspherical latent space

Position: Challenges and Future Directions of Data-Centric AI Alignment

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

Limited Preference Data? Learning Better Reward Model with Latent Space Synthesis

Out-of-Distribution Learning with Human Feedback

Safety-Aware Fine-Tuning of Large Language Models

HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection

When and How Does In-Distribution Label Help Out-of-Distribution Detection?

How Does Unlabeled Data Provably Help Out-of-Distribution Detection?

Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection

Non-Parametric Outlier Synthesis

OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection

Dream the Impossible: Outlier Imagination with Diffusion Models

Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection

SIREN: Shaping Representations for Detecting Out-of-Distribution Objects

VOS: Learning What You Don't Know by Virtual Outlier Synthesis

矿井主通风机监测和健康状态评估方法与系统研究

煤矿主要通风机风量传感器布置方法研究

PI-GNN: A Novel Perspective on Semi-Supervised Node Classification against Noisy Labels

Learning Diverse-Structured Networks for Adversarial Robustness

Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions

How to Save your Annotation Cost for Panoptic Segmentation?

Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography

矿用本安直流电源自动测试系统

无底柱分段崩落法在地下铁矿中的应用

地下矿山工程井巷掘进爆破技术探讨

Skillearn: Machine Learning Inspired by Humans' Learning Skills

Learning by Passing Tests, with Application to Neural Architecture Search

Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding

Small-Group Learning, with Application to Neural Architecture Search

Classification in Cryo-Electron Tomograms

Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss

Semi-supervised Macromolecule Structural Classification in Cellular Electron Cryo-Tomograms using 3D Autoencoding Classifier

RISING STARS IN DATA SCIENCE