| Lab: Large-scale alignment for chatbots S Sudalairaj, A Bhandwaldar, A Pareja, K Xu, DD Cox, A Srivastava arXiv preprint arXiv:2403.01081, 2024 | 24 | 2024 |
| Post-processing private synthetic data for improving utility on selected measures H Wang, S Sudalairaj, J Henning, K Greenewald, A Srivastava Advances in Neural Information Processing Systems 36, 64139-64154, 2023 | 9 | 2023 |
| On the importance of calibration in semi-supervised learning C Loh, R Dangovski, S Sudalairaj, S Han, L Han, L Karlinsky, M Soljacic, ... arXiv preprint arXiv:2210.04783, 2022 | 9 | 2022 |
| Coeviz 2: protein graphs derived from amino acid covariance D Corcoran, N Maltbie, S Sudalairaj, FN Baker, J Hirschfeld, A Porollo Frontiers in bioinformatics 1, 653681, 2021 | 7 | 2021 |
| Multi-symmetry ensembles: improving diversity and generalization via opposing symmetries C Loh, S Han, S Sudalairaj, R Dangovski, K Xu, F Wenzel, M Soljacic, ... International Conference on Machine Learning, 22614-22630, 2023 | 6 | 2023 |
| Lab: Large-scale alignment for chatbots, 2024 S Sudalairaj, A Bhandwaldar, A Pareja, K Xu, DD Cox, A Srivastava URL https://arxiv. org/abs/2403.01081, 0 | 6 | |
| Constructive assimilation: Boosting contrastive learning performance through view generation strategies L Han, S Han, S Sudalairaj, C Loh, R Dangovski, F Deng, P Agrawal, ... arXiv preprint arXiv:2304.00601, 2023 | 5 | 2023 |
| Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs A Pareja, NS Nayak, H Wang, K Killamsetty, S Sudalairaj, W Zhao, S Han, ... arXiv preprint arXiv:2412.13337, 2024 | 2 | 2024 |
| Grafting Vision Transformers J Park, K Kahatapitiya, D Kim, S Sudalairaj, Q Fan, MS Ryoo Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 1 | 2024 |
| Spatio-Temporal Analysis of EEG using Deep Learning S Sudalairaj University of Cincinnati, 2022 | 1 | 2022 |
| A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods I Puri, S Sudalairaj, G Xu, K Xu, A Srivastava arXiv preprint arXiv:2502.01618, 2025 | | 2025 |
| Dr. SoW: Density Ratio of Strong-over-weak LLMs for Reducing the Cost of Human Annotation in Preference Tuning G Xu, K Xu, S Sudalairaj, H Wang, A Srivastava arXiv preprint arXiv:2411.02481, 2024 | | 2024 |
| Fantastic LLMs for Preference Data Annotation and How to (not) Find Them G Xu, K Xu, S Sudalairaj, H Wang, A Srivastava arXiv e-prints, arXiv: 2411.02481, 2024 | | 2024 |
| Preference Data Annotation with Guided Density Ratios G Xu, K Xu, S Sudalairaj, A Srivastava | | |
| Training Mice to Compete with Elephants: A Guide for Customizing Small-Sized LLMs on Knowledge and Skills Data A Pareja, NS Nayak, H Wang, K Killamsetty, S Sudalairaj, W Zhao, S Han, ... The Thirteenth International Conference on Learning Representations, 0 | | |
| On Assimilating Learned Views in Contrastive Learning L Han, S Han, S Sudalairaj, C Loh, R Dangovski, P Agrawal, DN Metaxas, ... | | |
Akash SrivastavaMIT, IBM Research, University of EdinburghVerified email at mit.edu
