Qizhou Wang - RankMe

59 papers A* 15A 1Journal 42Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models. CoRR Fengpeng Li, Kemou Li, Qizhou Wang, Bo Han, Jiantao Zhou
2026	J	`jnl`	Deep reinforcement learning framework for the underground mine short-term production scheduling problem. Swarm Evol. Comput. Ning Li, Yi Ding, Bibo Dai, Liguan Wang, Jian Chang, Haiwang Ye, Qizhou Wang
2026	J	`jnl`	Explainable LLM Unlearning Through Reasoning. CoRR Junfeng Liao, Qizhou Wang, Shanshan Ye, Xin Yu, Ling Chen, Zhen Fang
2026	J	`jnl`	Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning. Trans. Mach. Learn. Res. Ali Taheri Ghahrizjani, Alireza Taban, Qizhou Wang, Shanshan Ye, Abdolreza Mirzaei, Tongliang Liu, Bo Han
2026	J	`jnl`	HIDFlowNet: A flow-based deep network for hyperspectral image denoising. Inf. Fusion Qizhou Wang, Li Pang, Xiangyong Cao, Zhiqiang Tian, Deyu Meng
2026	J	`jnl`	Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning. CoRR Zhuo Huang, Qizhou Wang, Ziming Hong, Shanshan Ye, Bo Han, Tongliang Liu
2025	A*	`conf`	Adaptive Localization of Knowledge Negation for Continual LLM Unlearning. ICML Abudukelimu Wuerkaixi, Qizhou Wang, Sen Cui, Wutong Xu, Bo Han, Gang Niu, Masashi Sugiyama, Changshui Zhang
2025	J	`jnl`	Arcadia: Toward a Full-Lifecycle Framework for Embodied Lifelong Learning. CoRR Minghe Gao, Juncheng Li, Yuze Lin, Xuqi Liu, Jiaming Ji, Xiaoran Pan, Zihan Xu, Xian Li, Mingjie Li, Wei Ji, Rong Wei, Rui Tang, Qizhou Wang, Kai Shen, Jun Xiao, Qi Wu, Siliang Tang, Yueting Zhuang
2025	J	`jnl`	EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget. CoRR Liang Chen, Xueting Han, Qizhou Wang, Bo Han, Jing Bai, Hinrich Schutze, Kam-Fai Wong
2025	A*	`conf`	Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning. ICML Puning Yang, Qizhou Wang, Zhuo Huang, Tongliang Liu, Chengqi Zhang, Bo Han
2025	J	`jnl`	Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning. CoRR Puning Yang, Qizhou Wang, Zhuo Huang, Tongliang Liu, Chengqi Zhang, Bo Han
2025	A*	`conf`	GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs. ICML Yue Wang, Qizhou Wang, Feng Liu, Wei Huang, Yali Du, Xiaojiang Du, Bo Han
2025	J	`jnl`	GRU: Mitigating the Trade-off between Unlearning and Retention for Large Language Models. CoRR Yue Wang, Qizhou Wang, Feng Liu, Wei Huang, Yali Du, Xiaojiang Du, Bo Han
2025	J	`jnl`	LLM Unlearning with LLM Beliefs. CoRR Kemou Li, Qizhou Wang, Yue Wang, Fengpeng Li, Jun Liu, Bo Han, Jiantao Zhou
2025	J	`jnl`	MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design. CoRR S. Rodionov, Arturo Burguete-Lopez, Maksim Makarenko, Qizhou Wang, Fedor Getman, Andrea Fratalocchi
2025	J	`jnl`	RML++: Regroup Median Loss for Combating Label Noise. Int. J. Comput. Vis. Fengpeng Li, Kemou Li, Qizhou Wang, Bo Han, Jinyu Tian, Jiantao Zhou
2025	A*	`conf`	Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. ICLR Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q. Weinberger
2025	J	`jnl`	Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. CoRR Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q. Weinberger
2025	J	`jnl`	Temporal-contextual Event Learning for Pedestrian Crossing Intent Prediction. CoRR Hongbin Liang, Hezhe Qiao, Wei Huang, Qizhou Wang, Mingsheng Shang, Lin Chen
2025	A*	`conf`	Towards Effective Evaluations and Comparisons for LLM Unlearning Methods. ICLR Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama
2025	J	`jnl`	Towards Understanding Valuable Preference Data for Large Language Model Alignment. CoRR Zizhuo Zhang, Qizhou Wang, Shanshan Ye, Jianing Zhu, Jiangchao Yao, Bo Han, Masashi Sugiyama
2025	J	`jnl`	W-DOE: Wasserstein Distribution-Agnostic Outlier Exposure. IEEE Trans. Pattern Anal. Mach. Intell. Qizhou Wang, Bo Han, Yang Liu, Chen Gong, Tongliang Liu, Jiming Liu
2025	J	`jnl`	What Is Preference Optimization Doing, How and Why? CoRR Yue Wang, Qizhou Wang, Zizhuo Zhang, Ang Li, Gang Niu, Bo Han, Masashi Sugiyama
2024	A*	`conf`	A Sober Look at the Robustness of CLIPs to Spurious Features. NeurIPS Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
2024	J	`jnl`	Combination prediction of underground mine rock drilling time based on seasonal and trend decomposition using Loess. Eng. Appl. Artif. Intell. Ning Li, Ding Liu, Liguan Wang, Haiwang Ye, Qizhou Wang, Dairong Yan, Shugang Zhao
2024	J	`jnl`	Do CLIPs Always Generalize Better than ImageNet Models? CoRR Qizhou Wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han, Tong Zhang
2024	J	`jnl`	Scheduling optimization of underground mine trackless transportation based on improved estimation of distribution algorithm. Expert Syst. Appl. Ning Li, Yahui Wu, Haiwang Ye, Liguan Wang, Qizhou Wang, Mingtao Jia
2024	—	`conf`	Temporal-Contextual Event Learning for Pedestrian Crossing Intent Prediction. ICONIP (5) Hongbin Liang, Hezhe Qiao, Wei Huang, Qizhou Wang, Mingsheng Shang, Lin Chen
2024	J	`jnl`	Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning. CoRR Qizhou Wang, Bo Han, Puning Yang, Jianing Zhu, Tongliang Liu, Masashi Sugiyama
2023	J	`jnl`	Are All Unseen Data Out-of-Distribution? CoRR Songming Zhang, Yuxiao Luo, Qizhou Wang, Haoang Chi, Weikai Li, Bo Han, Jinyan Li
2023	J	`jnl`	Artificial intelligence optical hardware empowers high-resolution hyperspectral video understanding at 1.2 Tb/s. CoRR Maksim Makarenko, Qizhou Wang, Arturo Burguete-Lopez, Silvio Giancola, Bernard Ghanem, Luca Passone, Andrea Fratalocchi
2023	J	`jnl`	Learning to Augment Distributions for Out-of-Distribution Detection. CoRR Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
2023	A*	`conf`	Learning to Augment Distributions for Out-of-distribution Detection. NeurIPS Qizhou Wang, Zhen Fang, Yonggang Zhang, Feng Liu, Yixuan Li, Bo Han
2023	A*	`conf`	Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. NeurIPS Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
2023	J	`jnl`	Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources. CoRR Haotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han
2023	A*	`conf`	Out-of-distribution Detection with Implicit Outlier Transformation. ICLR Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han
2023	J	`jnl`	Out-of-distribution Detection with Implicit Outlier Transformation. CoRR Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han
2023	J	`jnl`	Underground mine truck travel time prediction based on stacking integrated learning. Eng. Appl. Artif. Intell. Ning Li, Yahui Wu, Qizhou Wang, Haiwang Ye, Liguan Wang, Mingtao Jia, Shugang Zhao
2022	J	`jnl`	Improved estimation of canopy water status in maize using UAV-based digital and hyperspectral images. Comput. Electron. Agric. Meiyan Shu, Qizhou Wang, Shuaipeng Fei, Xiaohong Yang, Zhu Jinyu, Meng Lei, Baoguo Li, Yuntao Ma
2022	J	`jnl`	Instance-Dependent Positive and Unlabeled Learning With Labeling Bias Estimation. IEEE Trans. Pattern Anal. Mach. Intell. Chen Gong, Qizhou Wang, Tongliang Liu, Bo Han, Jane You, Jian Yang, Dacheng Tao
2022	A*	`conf`	Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders. CVPR Maksim Makarenko, Arturo Burguete-Lopez, Qizhou Wang, Fedor Getman, Silvio Giancola, Bernard Ghanem, Andrea Fratalocchi
2022	J	`jnl`	Real-time Hyperspectral Imaging in Hardware via Trained Metasurface Encoders. CoRR Maksim Makarenko, Arturo Burguete-Lopez, Qizhou Wang, Fedor Getman, Silvio Giancola, Bernard Ghanem, Andrea Fratalocchi
2022	A*	`conf`	Towards Lightweight Black-Box Attack Against Deep Neural Networks. NeurIPS Chenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian
2022	J	`jnl`	Towards Lightweight Black-Box Attacks against Deep Neural Networks. CoRR Chenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han, Xinmei Tian
2022	A*	`conf`	Watermarking for Out-of-distribution Detection. NeurIPS Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han
2022	J	`jnl`	Watermarking for Out-of-distribution Detection. CoRR Qizhou Wang, Feng Liu, Yonggang Zhang, Jing Zhang, Chen Gong, Tongliang Liu, Bo Han
2021	A	`conf`	Fraud Detection under Multi-Sourced Extremely Noisy Annotations. CIKM Chuang Zhang, Qizhou Wang, Tengfei Liu, Xun Lu, Jin Hong, Bo Han, Chen Gong
2021	A*	`conf`	Learning with Group Noise. AAAI Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han
2021	J	`jnl`	Learning with Group Noise. CoRR Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han
2021	A*	`conf`	Probabilistic Margins for Instance Reweighting in Adversarial Training. NeurIPS Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
2021	J	`jnl`	Probabilistic Margins for Instance Reweighting in Adversarial Training. CoRR Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
2021	J	`jnl`	Robust and Scalable Flat-Optics on Flexible Substrates via Evolutionary Neural Networks. Adv. Intell. Syst. Maksim Makarenko, Qizhou Wang, Arturo Burguete-Lopez, Fedor Getman, Andrea Fratalocchi
2021	J	`jnl`	Robust and Scalable Flat-Optics on Flexible Substrates via Evolutionary Neural Networks. Adv. Intell. Syst. Maksim Makarenko, Qizhou Wang, Arturo Burguete-Lopez, Fedor Getman, Andrea Fratalocchi
2021	J	`jnl`	SDA-GAN: Unsupervised Image Translation Using Spectral Domain Attention-Guided Generative Adversarial Network. CoRR Qizhou Wang, Maksim Makarenko
2021	A*	`conf`	Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model. AAAI Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong
2021	J	`jnl`	Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model. CoRR Qizhou Wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang, Chen Gong
2019	J	`jnl`	A game method for improving the interpretability of convolution neural network. CoRR Jinwei Zhao, Qizhou Wang, Fuqiang Zhang, Wanli Qiu, Yufei Wang, Yu Liu, Guo Xie, Weigang Ma, Bin Wang, Xinhong Hei
2018	J	`jnl`	How far from automatically interpreting deep learning. CoRR Jinwei Zhao, Qizhou Wang, Yufei Wang, Xinhong Hei, Yu Liu
2018	J	`jnl`	How to improve the interpretability of kernel learning. CoRR Jinwei Zhao, Qizhou Wang, Yufei Wang, Xinhong Hei, Yu Liu, Zhenghao Shi