| Discovering latent knowledge in language models without supervision C Burns*, H Ye*, D Klein, J Steinhardt The Eleventh International Conference on Learning Representations (ICLR 2023), 2022 | 275 | 2022 |
| DeePMD-kit v2: A software package for Deep Potential models J Zeng, D Zhang, D Lu, P Mo, Z Li, Y Chen, M Rynik, L Huang, Z Li, S Shi, ... The Journal of Chemical Physics, Volume 159, Issue 5, 2023 | 240 | 2023 |
| Towards Revealing the Mystery behind Chain of Thought: a Theoretical Perspective G Feng*, Y Gu*, B Zhang*, H Ye*, D He, L Wang Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2023 | 183 | 2023 |
| Towards a Theoretical Framework of Out-of-Distribution Generalization H Ye, C Xie, T Cai, R Li, Z Li, L Wang Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 2021 | 124 | 2021 |
| Monitoring ai-modified content at scale: A case study on the impact of chatgpt on ai conference peer reviews W Liang, Z Izzo, Y Zhang, H Lepp, H Cao, X Zhao, L Chen, H Ye, S Liu, ... The 41st International Conference on Machine Learning (ICML2024), 2024 | 94 | 2024 |
| In-context vectors: Making in context learning more effective and controllable through latent space steering S Liu, H Ye, L Xing, J Zou The 41st International Conference on Machine Learning (ICML2024), 2023 | 55 | 2023 |
| A computational framework for neural network-based variational Monte Carlo with Forward Laplacian R Li*, H Ye*, D Jiang, X Wen, C Wang, Z Li, X Li, D He, J Chen, W Ren, ... Nature Machine Intelligence, 1-11, 2024 | 24* | 2024 |
| Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise H Ye, J Zou, L Zhang The 26th International Conference on Artificial Intelligence and Statistics …, 2022 | 23 | 2022 |
| Out-of-distribution generalization analysis via influence function H Ye, C Xie, Y Liu, Z Li arXiv preprint arXiv:2101.08521, 2021 | 15 | 2021 |
| Risk variance penalization C Xie, H Ye, F Chen, Y Liu, R Sun, Z Li arXiv preprint arXiv:2006.07544, 2020 | 15 | 2020 |
| Selecting Large Language Model to Fine-tune via Rectified Scaling Law H Lin*, B Huang*, H Ye*, Q Chen, Z Wang, S Li, J Ma, X Wan, J Zou, ... The 41st International Conference on Machine Learning (ICML2024), 2024 | 10 | 2024 |
| On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness H Ye*, X Chen*, L Wang, SS Du The Fortieth International Conference on Machine Learning (ICML 2023); arXiv …, 2022 | 6 | 2022 |
| TFG: Unified training-free guidance for diffusion models H Ye, H Lin, J Han, M Xu, S Liu, Y Liang, J Ma, J Zou, S Ermon arXiv preprint arXiv:2409.15761, 2024 | 5 | 2024 |
| Reducing hallucinations in vision-language models via latent space steering S Liu, H Ye, L Xing, J Zou arXiv preprint arXiv:2410.15778, 2024 | 4 | 2024 |
| Geometric trajectory diffusion models J Han, M Xu, A Lou, H Ye, S Ermon arXiv preprint arXiv:2410.13027, 2024 | 2 | 2024 |
| DOF: Accelerating High-order Differential Operators with Forward Propagation R Li*, C Wang*, H Ye*, D He, L Wang arXiv preprint arXiv:2402.09730, 2024 | 2 | 2024 |
| Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews (arXiv: 2403.07183). arXiv W Liang, Z Izzo, Y Zhang, H Lepp, H Cao, X Zhao, L Chen, H Ye, S Liu, ... | 2 | 2024 |
| Squidiff: Predicting cellular development and responses to perturbations using a diffusion model S He, Y Zhu, DN Tavakol, H Ye, YH Lao, Z Zhu, C Xu, S Chauhan, G Garty, ... bioRxiv, 2024.11. 16.623974, 2024 | 1 | 2024 |
| TFG-Flow: Training-free Guidance in Multimodal Generative Flow H Lin, S Li, H Ye, Y Yang, S Ermon, Y Liang, J Ma arXiv preprint arXiv:2501.14216, 2025 | | 2025 |
| A Foundational Generative Model for Breast Ultrasound Image Analysis H Yu, Y Li, N Zhang, Z Niu, X Gong, Y Luo, H Ye, S He, Q Wu, W Qin, ... arXiv preprint arXiv:2501.06869, 2025 | | 2025 |
Liwei WangProfessor, Peking UniversityDirección de correo verificada de cis.pku.edu.cn
