LLM Unlearning with LLM Beliefs
K. Li, Q. Wang, Y. Wang, F. Li, J. Liu, B. Han, and J. Zhou
ICLR 2026
@inproceedings{li2026llm,
title={LLM Unlearning with LLM Beliefs},
author={Li, Kemou and Wang, Qizhou and Wang, Yue and Li, Fengpeng and Liu, Jun and Han, Bo and Zhou, Jiantao},
booktitle={International Conference on Learning Representations},
year={2026}
}
Towards Understanding Valuable Preference Data for Large Language Model Alignment
Z. Zhang, Q. Wang, S. Ye, J. Zhu, J. Yao, B. Han, and M. Sugiyama
ICLR 2026
@inproceedings{zhang2026towards,
title={Towards Understanding Valuable Preference Data for Large Language Model Alignment},
author={Zhang, Zizhuo and Wang, Qizhou and Ye, Shanshan and Zhu, Jianing and Yao, Jiangchao and Han, Bo and Sugiyama, Masashi},
booktitle={International Conference on Learning Representations},
year={2026}
}
AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models
F. Li, K. Li, Q. Wang, B. Han, and J. Zhou
ICLR 2026
@inproceedings{li2026AEGIS,
title={AEGIS: Adversarial Target–Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models},
author={Li, Fengpeng and Li, Kemou and Wang, Qizhou and Han, Bo and Zhou, Jiantao},
booktitle={International Conference on Learning Representations},
year={2026}
}
EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget
L. Chen, X. Han, Q. Wang, B. Han, J. Bai, H. Schutze, and KF Wong
ICLR 2026
@inproceedings{chen2026eepo,
title={EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget},
author={Liang Chen and Xueting Han and Qizhou Wang and Bo Han and Jing Bai and Hinrich Schutze and Kam-Fai Wong},
booktitle={International Conference on Learning Representations},
year={2026}
}
Explainable LLM Unlearning through Reasoning
J. Liao, Q. Wang, S. Ye, X. Yu, L. Chen, and Z. Fang
ICLR 2026
@inproceedings{liao2026explainable,
title={Explainable LLM Unlearning through Reasoning},
author={Liao, Junfeng and Wang, Qizhou and Ye, Shanshan and Yu, Xin and Chen, Ling and Fang, Zhen},
booktitle={International Conference on Learning Representations},
year={2026}
}
Adaptive Localization of Knowledge Negation for Continual LLM Unlearning
A. Wuerkaixi, Q. Wang, S. Cui, W. Xu, B. Han, G. Niu, M. Sugiyama, and C. Zhang
ICML 2025
@inproceedings{wuerkaixi2025adaptive,
title={Adaptive Localization of Knowledge Negation for Continual LLM Unlearning},
author={Wuerkaixi, Abudukelimu and Wang, Qizhou and Cui, Sen and Xu, Wutong and Han, Bo and Niu, Gang and Sugiyama, Masashi and Zhang, Changshui},
booktitle={International Conference on Machine Learning},
year={2025}
}
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
P. Yang, Q. Wang, Z. Huang, T. Liu, C. Zhang, and B. Han
ICML 2025
@inproceedings{yang2025exploring,
title={Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning},
author={Yang, Puning and Wang, Qizhou and Huang, Zhuo and Liu, Tongliang and Zhang, Chengqi and Han, Bo},
booktitle={International Conference on Machine Learning},
year={2025}
}
GRU: Mitigating the Trade-off between Unlearning and Retention for Large Language Models
Y. Wang, Q. Wang, F. Liu, W. Huang, Y. Du, X. Du, and B. Han
ICML 2025
@inproceedings{wang2025gru,
title={GRU: Mitigating the Trade-off between Unlearning and Retention for Large Language Models},
author={Wang, Yue and Wang, Qizhou and Liu, Feng and Huang, Wei and Du, Yali and Du, Xiaojiang and Han, Bo},
booktitle={International Conference on Machine Learning},
year={2025}
}
Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond
Q. Wang, J. Zhou, Z. Zhou, S. Shin, B. Han, and K. Q. Weinberger
ICLR 2025
@inproceedings{wang2025rethinking,
title={Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond},
author={Qizhou Wang and Jin Peng Zhou and Zhanke Zhou and Saebyeol Shin and Bo Han and Kilian Q Weinberger},
booktitle={International Conference on Learning Representations},
year={2025}
}
Towards Effective Evaluations and Comparison for LLM Unlearning Methods
Q. Wang, B. Han, P. Yang, J. Zhu, T. Liu, and M. Sugiyama
ICLR 2025
@inproceedings{wang2025towards,
title={Towards Effective Evaluations and Comparison for LLM Unlearning Methods},
author={Qizhou Wang and Bo Han and Puning Yang and Jianing Zhu and Tongliang Liu and Masashi Sugiyama},
booktitle={International Conference on Learning Representations},
year={2025}
}
A Sober Look at the Robustness of CLIPs to Spurious Features
Q. Wang, Y. Lin, Y. Chen, L. Schmidt, B. Han, and T. Zhang
NeurIPS 2024
@inproceedings{wang2024clip,
title={A Sober Look at the Robustness of CLIPs to Spurious Features},
author={Qizhou Wang and Yong Lin and Yongqiang Chen and Ludwig Schmidt and Bo Han and Tong Zhang},
booktitle={Advances in Neural Information Processing Systems},
year={2024}
}
Learning to Augment Distributions for Out-of-distribution Detection
Q. Wang, Z. Fang, Y. Zhang, F. Liu, Y. Li, and B. Han
NeurIPS 2023
@inproceedings{wang2023learning,
title={Learning to Augment Distributions for Out-of-distribution Detection},
author={Qizhou Wang and Zhen Fang and Yonggang Zhang and Feng Liu and Yixuan Li and Bo Han},
booktitle={Advances in Neural Information Processing Systems},
year={2023}
}
Out-of-distribution Detection with Unreliable Out-of-distribution Sources
H. Zheng, Q. Wang, Z. Fang, X. Xia, F. Liu, T. Liu, and B. Han
NeurIPS 2023
@inproceedings{zheng2023unreliable,
title={Out-of-distribution Detection with Unreliable Out-of-distribution Sources},
author={Haotian Zheng and Qizhou Wang and Zhen Fang and Xiaobo Xia and Feng Liu and Tongliang Liu and Bo Han},
booktitle={Advances in Neural Information Processing Systems},
year={2023}
}
Out-of-distribution Detection with Implicit Outlier Transformation
Q. Wang, J. Ye, F. Liu, Q. Dai, M. Kalander, T. Liu, J. Hao, and B. Han
ICLR 2023
@inproceedings{wang2023doe,
title={Out-of-distribution Detection with Implicit Outlier Transformation},
author={Qizhou Wang and Junjie Ye and Feng Liu and Quanyu Dai and Marcus Kalander and Tongliang Liu and Jianye Hao and Bo Han},
booktitle={International Conference on Learning Representations},
year={2023}
}
Watermarking for Out-of-distribution Detection
Q. Wang, F. Liu, Y. Zhang, J. Zhang, C. Gong, T. Liu, and B. Han
NeurIPS 2022
@inproceedings{wang2022watermark,
title={Watermarking for Out-of-distribution Detection},
author={Qizhou Wang and Feng Liu and Yonggang Zhang and Jing Zhang and Chen Gong and Tongliang Liu and Bo Han},
booktitle={Advances in Neural Information Processing Systems},
year={2022}
}
Probabilistic Margins for Instance Reweighting in Adversarial Training
Q. Wang, F. Liu, B. Han, T. Liu, C. Gong, G. Niu, M. Zhou, and M. Sugiyama
NeurIPS 2021
@inproceedings{wang2021mail,
title={Probabilistic Margins for Instance Reweighting in Adversarial Training},
author={Qizhou Wang and Feng Liu and Bo Han and Tongliang Liu and Chen Gong and Gang Niu and Mingyuan Zhou and Masashi Sugiyama},
booktitle={NeurIPS},
year={2021}
}
Tackling Instance-dependent Label Noise via a Universal Probabilistic Model
Q. Wang, B. Han, T. Liu, G. Niu, J. Yang, and C. Gong
AAAI 2021
@inproceedings{wang2021tackling_instance,
title={Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model},
author={Qizhou Wang and Bo Han and Tongliang Liu and Gang Niu and Jian Yang and Chen Gong},
booktitle={AAAI},
year={2021}
}
