| Fine-tuning language models with just forward passes S Malladi*, T Gao*, E Nichani, A Damian, JD Lee, D Chen, S Arora Advances in Neural Information Processing Systems 36, 53038-53075, 2023 | 140 | 2023 |
| LESS: Selecting influential data for targeted instruction tuning M Xia*, S Malladi*, S Gururangan, S Arora, D Chen International Conference on Machine Learning, 2024 | 94 | 2024 |
| On the validity of modeling SGD with stochastic differential equations (SDEs) Z Li, S Malladi, S Arora Advances in Neural Information Processing Systems 34, 12712-12725, 2021 | 89 | 2021 |
| A mathematical exploration of why language models help solve downstream tasks N Saunshi, S Malladi, S Arora International Conference on Learning Representations, 2021 | 84 | 2021 |
| EMDomics: a robust and powerful method for the identification of genes differentially expressed between heterogeneous classes S Nabavi, D Schmolze, M Maitituoheti, S Malladi, AH Beck Bioinformatics 32 (4), 533-541, 2016 | 75 | 2016 |
| 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 | 59 | 2023 |
| On the SDEs and scaling rules for adaptive gradient algorithms S Malladi*, K Lyu*, A Panigrahi, S Arora Advances in Neural Information Processing Systems 35, 7697-7711, 2022 | 34 | 2022 |
| Systematic analysis of sex-linked molecular alterations and therapies in cancer J Ma*, S Malladi*, AH Beck Scientific reports 6 (1), 19119, 2016 | 25 | 2016 |
| Trainable transformer in transformer A Panigrahi*, S Malladi*, M Xia, S Arora International Conference on Machine Learning, 2024 | 22 | 2024 |
| Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging I Banerjee, S Malladi, D Lee, A Depeursinge, M Telli, J Lipson, D Golden, ... Journal of medical imaging 5 (1), 011008-011008, 2018 | 22 | 2018 |
| MUSE: Machine unlearning six-way evaluation for language models W Shi, J Lee, Y Huang, S Malladi, J Zhao, A Holtzman, D Liu, ... GenLaw Workshop at International Conference on Machine Learning, 2024 | 21 | 2024 |
| Charxiv: Charting gaps in realistic chart understanding in multimodal llms Z Wang, M Xia, L He, H Chen, Y Liu, R Zhu, K Liang, X Wu, H Liu, ... Advances in Neural Information Processing Systems, 2024 | 11 | 2024 |
| FastNorm: improving numerical stability of deep network training with efficient normalization S Malladi, I Sharapov Women in Machine Learning Workshop at International Conference on Machine …, 2018 | 11 | 2018 |
| Preference Learning Algorithms Do Not Learn Preference Rankings A Chen, S Malladi, LH Zhang, X Chen, Q Zhang, R Ranganath, K Cho Advances in Neural Information Processing Systems, 2024 | 9 | 2024 |
| The marginal value of momentum for small learning rate sgd R Wang, S Malladi, T Wang, K Lyu, Z Li International Conference on Learning Representations, 2024 | 7 | 2024 |
| Provable unlearning in topic modeling and downstream tasks S Wei, S Malladi, S Arora, A Sanyal arXiv preprint arXiv:2411.12600, 2024 | | 2024 |
| Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws Y Jiang, A Zhou, Z Feng, S Malladi, JZ Kolter arXiv preprint arXiv:2410.11820, 2024 | | 2024 |
| Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization N Razin, S Malladi, A Bhaskar, D Chen, S Arora, B Hanin Fine-Tuning in Modern Machine Learning Workshop at NeurIPS 2024, 2024 | | 2024 |
| Progressive distillation improves feature learning via implicit curriculum A Panigrahi, B Liu, S Malladi, A Risteski, S Goel ICML 2024 Workshop on Mechanistic Interpretability, 0 | | |
| 2nd Workshop on Mathematical and Empirical Understanding of Foundation Models SM Xie, A Kumar, S Min, S Malladi, LM Dery, A Raghunathan, T Ma, ... ICLR 2024 Workshops, 0 | | |
Sanjeev AroraProfessor of Computer Science, Princeton UniversityVerified email at cs.princeton.edu