| Transformers learn higher-order optimization methods for in-context learning: A study with linear models D Fu, TQ Chen, R Jia, V Sharan arXiv preprint arXiv:2310.17086, 2023 | 13 | 2023 |
| Dreamsync: Aligning text-to-image generation with image understanding feedback J Sun*, D Fu*, Y Hu*, S Wang, R Rassin, DC Juan, D Alon, C Herrmann, ... arXiv preprint arXiv:2311.17946, 2023 | 10 | 2023 |
| Harnessing the Conditioning Sensorium for Improved Image Translation C Nederhood, N Kolkin, D Fu, J Salavon IEEE/CVF International Conference on Computer Vision (ICCV) 2021, 6752-6761, 2021 | 5 | 2021 |
| Comparison of two gradient computation methods in Python SHK Narayanan, P Hovland, K Kulshreshtha, D Nagarkar, K MacIntyre, ... NIPS/NeurIPS 2017 Workshop Autodiff, 2017 | 2 | 2017 |
| SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples D Fu, A Godbole, R Jia Empirical Methods in Natural Language Processing (EMNLP) 2023, 2023 | 1 | 2023 |
| IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations D Fu, G Khalighinejad, O Liu, B Dhingra, D Yogatama, R Jia, ... arXiv preprint arXiv:2404.01266, 2024 | | 2024 |
| Simplicity Bias of Transformers to Learn Low Sensitivity Functions B Vasudeva*, D Fu*, T Zhou, E Kau, Y Huang, V Sharan arXiv preprint arXiv:2403.06925, 2024 | | 2024 |
| DeLLMa: A Framework for Decision Making Under Uncertainty with Large Language Models O Liu*, D Fu*, D Yogatama, W Neiswanger arXiv preprint arXiv:2402.02392, 2024 | | 2024 |
| Topological Regularization for Dense Prediction D Fu, BJ Nelson IEEE International Conference on Machine Learning and Applications (ICMLA) 2022, 2022 | | 2022 |
Robin JiaUniversity of Southern CaliforniaVerified email at usc.edu
