| Adamerging: Adaptive model merging for multi-task learning E Yang, Z Wang, L Shen, S Liu, G Guo, X Wang, D Tao The Twelfth International Conference on Learning Representations, 2024 | 98 | 2024 |
| Towards faithful neural table-to-text generation with content-matching constraints Z Wang, X Wang, B An, D Yu, C Chen Annual Conference of the Association for Computational Linguistics, 2020 | 96 | 2020 |
| A comprehensive survey of forgetting in deep learning beyond continual learning Z Wang, E Yang, L Shen, H Huang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 54 | 2024 |
| Learning diverse stochastic human-action generators by learning smooth latent transitions Z Wang, P Yu, Y Zhao, R Zhang, Y Zhou, J Yuan, C Chen Proceedings of the AAAI conference on artificial intelligence 34 (07), 12281 …, 2020 | 54 | 2020 |
| Improving task-free continual learning by distributionally robust memory evolution Z Wang, L Shen, L Fang, Q Suo, T Duan, M Gao International conference on machine learning, 22985-22998, 2022 | 52 | 2022 |
| Learning to learn and remember super long multi-domain task sequence Z Wang, L Shen, T Duan, D Zhan, L Fang, M Gao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 31 | 2022 |
| Repulsive attention: Rethinking multi-head attention as bayesian inference B An, J Lyu, Z Wang, C Li, C Hu, F Tan, R Zhang, Y Hu, C Chen The 2020 Conference on Empirical Methods in Natural Language Processing, 2020 | 30 | 2020 |
| Representation Surgery for Multi-Task Model Merging E Yang, L Shen, Z Wang, G Guo, X Chen, X Wang, D Tao International Conference on Machine Learning, 2024 | 29 | 2024 |
| An efficient dataset condensation plugin and its application to continual learning E Yang, L Shen, Z Wang, T Liu, G Guo Advances in Neural Information Processing Systems 36, 2023 | 29 | 2023 |
| Meta-learning without data via wasserstein distributionally-robust model fusion Z Wang, X Wang, L Shen, Q Suo, K Song, D Yu, Y Shen, M Gao Uncertainty in Artificial Intelligence, 2045-2055, 2022 | 27 | 2022 |
| Meta-learning with neural tangent kernels Y Zhou*, Z Wang*, J Xian, C Chen, J Xu International Conference on Learning Representations, 2021 | 26 | 2021 |
| Meta learning on a sequence of imbalanced domains with difficulty awareness Z Wang, T Duan, L Fang, Q Suo, M Gao Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 25 | 2021 |
| A Unified and General Framework for Continual Learning Z Wang, Y Li, L Shen, H Huang The Twelfth International Conference on Learning Representations, 2024 | 23 | 2024 |
| Bayesian meta sampling for fast uncertainty adaptation Z Wang, Y Zhao, P Yu, R Zhang, C Chen International Conference on Learning Representations, 2020 | 23 | 2020 |
| Data augmented flatness-aware gradient projection for continual learning E Yang, L Shen, Z Wang, S Liu, G Guo, X Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 22 | 2023 |
| Improving Non-Transferable Representation Learning by Harnessing Content and Style Z Hong, Z Wang, L Shen, Y Yao, Z Huang, S Chen, C Yang, M Gong, ... The Twelfth International Conference on Learning Representations, 2024 | 21 | 2024 |
| Meta-learning with less forgetting on large-scale non-stationary task distributions Z Wang, L Shen, L Fang, Q Suo, D Zhan, T Duan, M Gao European Conference on Computer Vision, 221-238, 2022 | 19 | 2022 |
| Location augmentation for cnn Z Wang, O Veksler arXiv preprint arXiv:1807.07044, 2018 | 17 | 2018 |
| Learning to Learn from APIs: Black-Box Data-Free Meta-Learning Z Hu, L Shen, Z Wang, B Wu, C Yuan, D Tao International Conference on Machine Learning, 2023 | 15 | 2023 |
| Metamix: Towards corruption-robust continual learning with temporally self-adaptive data transformation Z Wang, L Shen, D Zhan, Q Suo, Y Zhu, T Duan, M Gao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 13 | 2023 |