| Harnessing the power of infinitely wide deep nets on small-data tasks S Arora, SS Du, Z Li, R Salakhutdinov, R Wang, D Yu arXiv preprint arXiv:1910.01663, 2019 | 197 | 2019 |
| Enhanced convolutional neural tangent kernels Z Li, R Wang, D Yu, SS Du, W Hu, R Salakhutdinov, S Arora arXiv preprint arXiv:1911.00809, 2019 | 140 | 2019 |
| Simple and effective regularization methods for training on noisily labeled data with generalization guarantee W Hu, Z Li, D Yu arXiv preprint arXiv:1905.11368, 2019 | 91 | 2019 |
| A kernel-based view of language model fine-tuning S Malladi, A Wettig, D Yu, D Chen, S Arora International Conference on Machine Learning, 23610-23641, 2023 | 68 | 2023 |
| Tensor programs vi: Feature learning in infinite-depth neural networks G Yang, D Yu, C Zhu, S Hayou arXiv preprint arXiv:2310.02244, 2023 | 41* | 2023 |
| A partisan districting protocol with provably nonpartisan outcomes W Pegden, AD Procaccia, D Yu arXiv preprint arXiv:1710.08781, 2017 | 39 | 2017 |
| Keeping llms aligned after fine-tuning: The crucial role of prompt templates K Lyu, H Zhao, X Gu, D Yu, A Goyal, S Arora arXiv preprint arXiv:2402.18540, 2024 | 26 | 2024 |
| Skill-Mix: A flexible and expandable family of evaluations for AI models D Yu, S Kaur, A Gupta, J Brown-Cohen, A Goyal, S Arora arXiv preprint arXiv:2310.17567, 2023 | 26 | 2023 |
| Characterization of group-strategyproof mechanisms for facility location in strictly convex space P Tang, D Yu, S Zhao Proceedings of the 21st ACM Conference on Economics and Computation, 133-157, 2020 | 23 | 2020 |
| Fast mixing of stochastic gradient descent with normalization and weight decay Z Li, T Wang, D Yu Advances in Neural Information Processing Systems 35, 9233-9248, 2022 | 21 | 2022 |
| Fair rent division on a budget A Procaccia, R Velez, D Yu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 18 | 2018 |
| Phi-4 technical report M Abdin, J Aneja, H Behl, S Bubeck, R Eldan, S Gunasekar, M Harrison, ... arXiv preprint arXiv:2412.08905, 2024 | 13 | 2024 |
| Conceptmix: A compositional image generation benchmark with controllable difficulty X Wu, D Yu, Y Huang, O Russakovsky, S Arora arXiv preprint arXiv:2408.14339, 2024 | 8 | 2024 |
| New definitions and evaluations for saliency methods: Staying intrinsic, complete and sound A Gupta, N Saunshi, D Yu, K Lyu, S Arora Advances in Neural Information Processing Systems 35, 33120-33133, 2022 | 7 | 2022 |
| Ai-assisted generation of difficult math questions V Shah, D Yu, K Lyu, S Park, J Yu, Y He, NR Ke, M Mozer, Y Bengio, ... arXiv preprint arXiv:2407.21009, 2024 | 5 | 2024 |
| Can Models Learn Skill Composition from Examples? H Zhao, S Kaur, D Yu, A Goyal, S Arora arXiv preprint arXiv:2409.19808, 2024 | 1 | 2024 |
| Balanced Outcomes in Wage Bargaining. P Tang, D Yu AAMAS, 2091-2093, 2018 | 1 | 2018 |
| Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs? S Park, A Panigrahi, Y Cheng, D Yu, A Goyal, S Arora arXiv preprint arXiv:2501.02669, 2025 | | 2025 |
| Efficient Scaling of Large Models: Principles in Optimization and Data Aspects D Yu Princeton University, 2024 | | 2024 |
Sanjeev AroraProfessor of Computer Science, Princeton UniversityVerified email at princeton.edu