| Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation H Wang, H Zhao, B Li International Conference on Machine Learning (ICML), 2021 | 113 | 2021 |
| Mitigating the Alignment Tax or RLHF Y Lin, H Lin, W Xiong, S Diao, J Liu, J Zhang, R Pan, H Wang, W Hu, ... arXiv preprint arXiv:2309.06256, 2023 | 110* | 2023 |
| RLHF Workflow: From Reward Modeling to Online RLHF H Dong, W Xiong, B Pang, H Wang, H Zhao, Y Zhou, N Jiang, D Sahoo, ... arXiv preprint arXiv:2405.07863, 2024 | 89 | 2024 |
| Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts H Wang, W Xiong, T Xie, H Zhao, T Zhang arXiv preprint arXiv:2406.12845, 2024 | 86 | 2024 |
| SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding H Wang, PKA Vasu, F Faghri, R Vemulapalli, M Farajtabar, S Mehta, ... arXiv preprint arXiv:2310.15308, 2023 | 75 | 2023 |
| Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning H Wang, Y Wang, R Sun, B Li Computer Vision and Pattern Recognition (CVPR), 2022 | 71* | 2022 |
| Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards H Wang, Y Lin, W Xiong, R Yang, S Diao, S Qiu, H Zhao, T Zhang ACL 2024, 2024 | 62 | 2024 |
| Understanding Gradual Domain Adaptation: Improved Analysis, Optimal Path and Beyond H Wang, B Li, H Zhao International Conference on Machine Learning (ICML) 162, 22784-22801, 2022 | 43 | 2022 |
| Provable Domain Generalization via Invariant-Feature Subspace Recovery H Wang, H Si, B Li, H Zhao International Conference on Machine Learning (ICML), 2022 | 35 | 2022 |
| Cosmos World Foundation Model Platform for Physical AI N Agarwal, A Ali, M Bala, Y Balaji, E Barker, T Cai, P Chattopadhyay, ... arXiv preprint arXiv:2501.03575, 2025 | 13 | 2025 |
| Predicting Properties of Quantum Systems with Conditional Generative Models H Wang, M Weber, J Izaac, CYY Lin arXiv preprint arXiv:2211.16943, 2022 | 11 | 2022 |
| Learning positive functions with pseudo mirror descent Y Yang, H Wang, N Kiyavash, N He Advances in Neural Information Processing Systems (NeurIPS), 2019 | 11 | 2019 |
| Gradual Domain Adaptation: Theory and Algorithms Y He, H Wang, B Li, H Zhao Journal of Machine Learning Research, 2024 | 10 | 2024 |
| Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation System M Ye, R Jiang, H Wang, D Choudhary, X Du, B Bhushanam, A Mokhtari, ... Conference on Uncertainty in Artificial Intelligence (UAI), 2022 | 6 | 2022 |
| Invariant Feature Subspace Recovery for Multi-Class Classification G Balasubramaniam, H Wang, H Zhao NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 2 | 2022 |
| Semi-Supervised Reward Modeling via Iterative Self-Training Y He, H Wang, Z Jiang, A Papangelis, H Zhao arXiv preprint arXiv:2409.06903, 2024 | 1 | 2024 |
| Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms H Wang, G Balasubramaniam, H Si, B Li, H Zhao arXiv preprint arXiv:2311.00966, 2023 | 1 | 2023 |
| Enhancing Compositional Generalization via Compositional Feature Alignment H Wang, H Si, H Shao, H Zhao Transactions on Machine Learning Research (TMLR), 2024 | | 2024 |
Han ZhaoDepartment of Computer Science, University of Illinois Urbana-ChampaignВерификована је имејл адреса на illinois.edu