| Jailbreak and guard aligned language models with only few in-context demonstrations Z Wei, Y Wang, A Li, Y Mo, Y Wang arXiv preprint arXiv:2310.06387, 2023 | 148 | 2023 |
| Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap Y Wang*, Q Zhang*, Y Wang, J Yang, Z Lin ICLR 2022, 2022 | 126 | 2022 |
| Dissecting the diffusion process in linear graph convolutional networks Y Wang, Y Wang, J Yang, Z Lin NeurIPS 2021, 2021 | 76 | 2021 |
| How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders Q Zhang*, Y Wang*, Y Wang NeurIPS 2022 Spotlight, 2022 | 64 | 2022 |
| When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture Y Mo, D Wu, Y Wang, Y Guo, Y Wang NeurIPS 2022 Spotlight, 2022 | 58 | 2022 |
| CFA: Class-wise Calibrated Fair Adversarial Training Z Wei, Y Wang, Y Guo, Y Wang CVPR 2023, 2023 | 56 | 2023 |
| Optimization-induced graph implicit nonlinear diffusion Q Chen, Y Wang, Y Wang, J Yang, Z Lin ICML 2022, 2022 | 37 | 2022 |
| ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond X Guo*, Y Wang*, T Du*, Y Wang ICLR 2023, 2023 | 36 | 2023 |
| Residual relaxation for multi-view representation learning Y Wang, Z Geng, F Jiang, C Li, Y Wang, J Yang, Z Lin NeurIPS 2021, 2021 | 35 | 2021 |
| G CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters M Li, X Guo, Y Wang, Y Wang, Z Lin ICML 2022, 2022 | 24 | 2022 |
| A Message Passing Perspective on Learning Dynamics of Contrastive Learning Y Wang*, Q Zhang*, T Du, J Yang, Z Lin, Y Wang ICLR 2023, 2023 | 20 | 2023 |
| Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning R Luo*, Y Wang*, Y Wang ICLR 2023, 2023 | 20 | 2023 |
| On the Generalization of Multi-modal Contrastive Learning Q Zhang*, Y Wang*, Y Wang ICML 2023, 2023 | 19 | 2023 |
| Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism Z Zhuo*, Y Wang*, J Ma, Y Wang ICLR 2023, 2023 | 19 | 2023 |
| Do Generated Data Always Help Contrastive Learning? Y Wang*, J Zhang*, Y Wang ICLR 2024, 2024 | 17 | 2024 |
| Adversarial examples are not real features A Li*, Y Wang*, Y Guo, Y Wang NeurIPS 2023, 2023 | 15 | 2023 |
| Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Y Wang*, L Li*, J Yang, Z Lin, Y Wang NeurIPS 2023, 2023 | 13 | 2023 |
| Architecture matters: Uncovering implicit mechanisms in graph contrastive learning X Guo*, Y Wang*, Z Wei, Y Wang NeurIPS 2023, 2023 | 12 | 2023 |
| Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding J Ma*, Y Wang*, Y Wang NeurIPS 2023, 2023 | 11 | 2023 |
| Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors Q Wang*, Y Wang*, H Zhu, Y Wang NeurIPS 2022 Spotlight, 2022 | 11 | 2022 |
Yisen WangAssistant Professor, Peking UniversityVerified email at pku.edu.cn
