| How does mixup help with robustness and generalization? L Zhang, Z Deng, K Kawaguchi, A Ghorbani, J Zou arXiv preprint arXiv:2010.04819, 2020 | 291 | 2020 |
| Analyzing and mitigating object hallucination in large vision-language models Y Zhou, C Cui, J Yoon, L Zhang, Z Deng, C Finn, M Bansal, H Yao arXiv preprint arXiv:2310.00754, 2023 | 196 | 2023 |
| An unconstrained layer-peeled perspective on neural collapse W Ji, Y Lu, Y Zhang, Z Deng, WJ Su arXiv preprint arXiv:2110.02796, 2021 | 90 | 2021 |
| How does information bottleneck help deep learning? K Kawaguchi, Z Deng, X Ji, J Huang International Conference on Machine Learning, 16049-16096, 2023 | 68 | 2023 |
| When and how mixup improves calibration L Zhang, Z Deng, K Kawaguchi, J Zou International Conference on Machine Learning, 26135-26160, 2022 | 68 | 2022 |
| Adversarial training helps transfer learning via better representations Z Deng, L Zhang, K Vodrahalli, K Kawaguchi, JY Zou Advances in Neural Information Processing Systems 34, 25179-25191, 2021 | 60 | 2021 |
| The power of contrast for feature learning: A theoretical analysis W Ji, Z Deng, R Nakada, J Zou, L Zhang Journal of Machine Learning Research 24 (330), 1-78, 2023 | 41 | 2023 |
| Toward better generalization bounds with locally elastic stability Z Deng, H He, W Su International Conference on Machine Learning, 2590-2600, 2021 | 41 | 2021 |
| Understanding multimodal contrastive learning and incorporating unpaired data R Nakada, HI Gulluk, Z Deng, W Ji, J Zou, L Zhang International Conference on Artificial Intelligence and Statistics, 4348-4380, 2023 | 34 | 2023 |
| Happymap: A generalized multi-calibration method Z Deng, C Dwork, L Zhang arXiv preprint arXiv:2303.04379, 2023 | 28 | 2023 |
| Robustness implies generalization via data-dependent generalization bounds K Kawaguchi, Z Deng, K Luh, J Huang International conference on machine learning, 10866-10894, 2022 | 28 | 2022 |
| Improving adversarial robustness via unlabeled out-of-domain data Z Deng, L Zhang, A Ghorbani, J Zou International Conference on Artificial Intelligence and Statistics, 2845-2853, 2021 | 27 | 2021 |
| Learning and forgetting unsafe examples in large language models J Zhao, Z Deng, D Madras, J Zou, M Ren arXiv preprint arXiv:2312.12736, 2023 | 26 | 2023 |
| Decision-aware conditional gans for time series data H Sun, Z Deng, H Chen, D Parkes Proceedings of the Fourth ACM International Conference on AI in Finance, 36-45, 2023 | 26 | 2023 |
| Last-layer fairness fine-tuning is simple and effective for neural networks Y Mao, Z Deng, H Yao, T Ye, K Kawaguchi, J Zou arXiv preprint arXiv:2304.03935, 2023 | 23 | 2023 |
| Representation via representations: Domain generalization via adversarially learned invariant representations Z Deng, F Ding, C Dwork, R Hong, G Parmigiani, P Patil, P Sur arXiv preprint arXiv:2006.11478, 2020 | 23 | 2020 |
| Fifa: Making fairness more generalizable in classifiers trained on imbalanced data Z Deng, J Zhang, L Zhang, T Ye, Y Coley, WJ Su, J Zou arXiv preprint arXiv:2206.02792, 2022 | 18 | 2022 |
| An economic solution to copyright challenges of generative ai JT Wang, Z Deng, H Chiba-Okabe, B Barak, WJ Su arXiv preprint arXiv:2404.13964, 2024 | 16 | 2024 |
| Interpreting robust optimization via adversarial influence functions Z Deng, C Dwork, J Wang, L Zhang International Conference on Machine Learning, 2464-2473, 2020 | 16 | 2020 |
| Investigating fairness disparities in peer review: A language model enhanced approach J Zhang, H Zhang, Z Deng, D Roth arXiv preprint arXiv:2211.06398, 2022 | 15 | 2022 |
