| Rethinking architecture selection in differentiable NAS R Wang, M Cheng, X Chen, X Tang, CJ Hsieh International Conference on Learning Representations, 2021 | 202 | 2021 |
| DrNAS: Dirichlet Neural Architecture Search X Chen*, R Wang*, M Cheng*, X Tang, CJ Hsieh International Conference on Learning Representations, 2021 | 143 | 2021 |
| Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory J Cui, R Wang, S Si, CJ Hsieh International Conference on Machine Learning, 2023 | 93 | 2023 |
| FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning Y Xiong*, R Wang*, M Cheng, F Yu, CJ Hsieh The IEEE Computer Vision and Pattern Recognition Conference (CVPR), 2023 | 81 | 2023 |
| DC-BENCH: Dataset Condensation Benchmark J Cui, R Wang, S Si, CJ Hsieh Advances in Neural Information Processing Systems, 2022 | 66 | 2022 |
| Generalizing Few-Shot NAS with Gradient Matching S Hu*, R Wang*, H Lanqing, Z Li, CJ Hsieh, J Feng International Conference on Learning Representations, 2022 | 28 | 2022 |
| RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving R Wang, X Chen, M Cheng, X Tang, CJ Hsieh Proceedings of IEEE International Conference on Computer Vision, 2021 | 17 | 2021 |
| Learning to Schedule Learning rate with Graph Neural Networks Y Xiong, LC Lan, X Chen, R Wang, CJ Hsieh International Conference on Learning Representations, 2022 | 16 | 2022 |
| DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers X Li, R Wang, M Cheng, T Zhou, CJ Hsieh arXiv preprint arXiv:2402.16914, 2024 | 12 | 2024 |
| Efficient Non-Parametric Optimizer Search for Diverse Tasks R Wang, Y Xiong, M Cheng, CJ Hsieh Advances in Neural Information Processing Systems, 2022 | 7 | 2022 |
| MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries? X Li, H Zhou, R Wang, T Zhou, M Cheng, CJ Hsieh arXiv preprint arXiv:2406.17806, 2024 | 1 | 2024 |
| Understanding the Impact of Negative Prompts: When and How Do They Take Effect? Y Ban, R Wang, T Zhou, M Cheng, B Gong, CJ Hsieh European Conference on Computer Vision (ECCV), 2024 | 1 | 2024 |
| One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts R Wang, S An, M Cheng, T Zhou, SJ Hwang, CJ Hsieh International Conference on Machine Learning, 2024 | 1* | 2024 |
| MuLan: Multimodal-LLM Agent for Progressive Multi-Object Diffusion S Li, R Wang, CJ Hsieh, M Cheng, T Zhou arXiv preprint arXiv:2402.12741, 2024 | 1 | 2024 |
| Large Language Models are Interpretable Learners R Wang, S Si, F Yu, D Wiesmann, CJ Hsieh, I Dhillon arXiv preprint arXiv:2406.17224, 2024 | | 2024 |
| Ameliorate Spurious Correlations in Dataset Condensation J Cui, R Wang, Y Xiong, CJ Hsieh International Conference on Machine Learning, 2024 | | 2024 |
| The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise Y Ban, R Wang, T Zhou, B Gong, CJ Hsieh, M Cheng arXiv preprint arXiv:2406.01970, 2024 | | 2024 |
| On Discrete Prompt Optimization for Diffusion Models R Wang, T Liu, CJ Hsieh, B Gong International Conference on Machine Learning, 2024 | | 2024 |
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
