| Remax: A simple, effective, and efficient reinforcement learning method for aligning large language models Z Li, T Xu, Y Zhang, Z Lin, Y Yu, R Sun, ZQ Luo International Conference on Machine Learning, 2024, 2023 | 187* | 2023 |
| Adam Can Converge Without Any Modification On Update Rules Y Zhang, C Chen, N Shi, R Sun, ZQ Luo Advances in Neural Information Processing Systems, 2022, 2022 | 134 | 2022 |
| Adam-mini: Use Fewer Learning Rates To Gain More Y Zhang, C Chen, Z Li, T Ding, C Wu, DP Kingma, Y Ye, ZQ Luo, R Sun International Conference on Learning Representations, 2025, 2024 | 101* | 2024 |
| Why Transformers Need Adam: A Hessian Perspective Y Zhang, C Chen, T Ding, Z Li, R Sun, ZQ Luo Advances in Neural Information Processing Systems, 2024, 2024 | 95 | 2024 |
| Provable Adaptivity of Adam under Non-uniform Smoothness B Wang, Y Zhang, H Zhang, Q Meng, ZM Ma, TY Liu, W Chen ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024, 2024 | 66 | 2024 |
| HyperDQN: A randomized exploration method for deep reinforcement learning Z Li, Y Li, Y Zhang, T Zhang, ZQ Luo International Conference on Learning Representations, 2022, 2021 | 26 | 2021 |
| When Expressivity Meets Trainability: Fewer than Neurons Can Work J Zhang, Y Zhang, M Hong, R Sun, ZQ Luo Advances in Neural Information Processing Systems, 2021, 2021 | 16 | 2021 |
| Fast QLB algorithm and hypothesis tests in logistic model for ophthalmologic bilateral correlated data YQ Lin, YS Zhang, GL Tian, CX Ma Journal of Biopharmaceutical Statistics 31 (1), 91-107, 2021 | 9 | 2021 |
| Towards quantifying the hessian structure of neural networks Z Dong, Y Zhang, J Yao, R Sun arXiv preprint arXiv:2505.02809, 2025 | 7 | 2025 |
| Finite horizon optimization: Framework and applications Y Zhang, D Rybin, ZQ Luo arXiv preprint arXiv:2412.21068, 2024 | 2 | 2024 |
| Does Adam Converge and When? Y Zhang, C Chen, ZQ Luo ICLR 2022 Blog Track, 2022 | 2 | 2022 |
| Can Be Faster D Rybin, Y Zhang, ZQ Luo arXiv preprint arXiv:2505.09814, 2025 | 1 | 2025 |