| 2026 | AAAI | Robust Learning from Noisily Labeled Long-Tailed Data via Fairness Regularizer. | Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu |
| 2026 | ACL | OFFSIDE: Benchmarking Unlearning Misinformation in Multimodal Large Language Models. | Hao Zheng, Zirui Pang, Ling Li, Zhijie Deng, Yuhan Pu, Zhaowei Zhu, Xiaobo Xia, Jiaheng Wei |
| 2025 | ICLR | Improving Data Efficiency via Curating LLM-Driven Rating Systems. | Jinlong Pang, Jiaheng Wei, Ankit Shah, Zhaowei Zhu, Yaxuan Wang, Chen Qian, Yang Liu, Yujia Bao, Wei Wei |
| 2025 | ICML | Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning. | Jinlong Pang, Na Di, Zhaowei Zhu, Jiaheng Wei, Hao Cheng, Chen Qian, Yang Liu |
| 2025 | KDD | Noise-Resilient Point-wise Anomaly Detection in Time Series Using Weak Segment Labels. | Yaxuan Wang, Hao Cheng, Jing Xiong, Qingsong Wen, Han Jia, Ruixuan Song, Liyuan Zhang, Zhaowei Zhu, Yang Liu |
| 2024 | AAAI | FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning. | Xinyuan Ji, Zhaowei Zhu, Wei Xi, Olga Gadyatskaya, Zilong Song, Yong Cai, Yang Liu |
| 2024 | ECCV | Federated Learning with Local Openset Noisy Labels. | Zonglin Di, Zhaowei Zhu, Xiaoxiao Li, Yang Liu |
| 2024 | ICLR | Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models. | Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu |
| 2024 | IJCNN | Periodicity Association Based Contrastive Learning for Time Series Anomaly Detection. | Jiawei Xu, Zhaowei Zhu, Weiwei Ye, Ning Gui |
| 2024 | SMC | MVOD: A Multi-View Outlier Detection Method with Single-Feature View Augmentation. | Zhaowei Zhu, Zhu Chen, Ning Gui, Jiawei Xu, Yun Lei, Dongdong Li |
| 2023 | ICLR | Mitigating Memorization of Noisy Labels via Regularization between Representations. | Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu |
| 2023 | ICML | Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes. | Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Hang Li, Yang Liu |
| 2023 | KDD | To Aggregate or Not? Learning with Separate Noisy Labels. | Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu |
| 2022 | ICLR | Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. | Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu |
| 2022 | ICLR | The Rich Get Richer: Disparate Impact of Semi-Supervised Learning. | Zhaowei Zhu, Tianyi Luo, Yang Liu |
| 2022 | ICML | Detecting Corrupted Labels Without Training a Model to Predict. | Zhaowei Zhu, Zihao Dong, Yang Liu |
| 2022 | ICML | Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features. | Zhaowei Zhu, Jialu Wang, Yang Liu |
| 2021 | CVPR | A Second-Order Approach to Learning With Instance-Dependent Label Noise. | Zhaowei Zhu, Tongliang Liu, Yang Liu |
| 2021 | ICLR | Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. | Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu |
| 2021 | ICML | Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels. | Zhaowei Zhu, Yiwen Song, Yang Liu |
| 2021 | SIGMETRICS | Federated Bandit: A Gossiping Approach. | Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu |
| 2019 | GLOBECOM | Learn to Offload in Mobile Edge Computing. | Ting Liu, Zhaowei Zhu, Junrong Gu, Xiliang Luo |
| 2018 | GLOBECOM | Sparse Spectrum Reuse in HetNets with Relays. | Shengda Jin, Zhaowei Zhu, Cong Shen, Sadiq Ali, Hua Qian, Xiliang Luo |
| 2018 | GLOBECOM | Learn and Pick Right Nodes to Offload. | Zhaowei Zhu, Ting Liu, Shengda Jin, Xiliang Luo |
| 2018 | HCI | Research on Τest of Anti-G Suits Αirbag Pressure. | Yi Ding, Zhaowei Zhu, Yandong Wang, Zhongji Zhang, Kaiyuan Song, Li Ding |
| 2018 | VTC | CSI Based High Accuracy Device Free Passive Localization System. | Yuge Liu, Wenhui Xiong, Zhaowei Zhu, Shaoqian Li |
| 2017 | GLOBECOM | Optimal Time Reuse in Cooperative D2D Relaying Networks. | Zhaowei Zhu, Shengda Jin, Yu Zeng, Honglin Hu, Xiliang Luo |