| Ground: A Data Context Service. JM Hellerstein, V Sreekanti, JE Gonzalez, J Dalton, A Dey, S Nag, ... CIDR, 2017 | 129 | 2017 |
| A big data analysis framework using apache spark and deep learning A Gupta, HK Thakur, R Shrivastava, P Kumar, S Nag 2017 IEEE international conference on data mining workshops (ICDMW), 9-16, 2017 | 74 | 2017 |
| Incorporating bilingual dictionaries for low resource semi-supervised neural machine translation S Nag, M Kale, V Lakshminarasimhan, S Singhavi Limited Labeled Data (LLD) Workshop at ICLR 2019, 2020 | 14 | 2020 |
| Rose: Robust caches for amazon product search C Luo, V Lakshman, A Shrivastava, T Cao, S Nag, R Goutam, H Lu, ... Companion Proceedings of the Web Conference 2022, 89-93, 2022 | 8 | 2022 |
| Large Language Models in Healthcare: A Comprehensive Benchmark F Liu, H Zhou, Y Hua, O Rohanian, L Clifton, D Clifton medRxiv, 2024.04. 24.24306315, 2024 | 7 | 2024 |
| Multi-class instance-incremental framework for classification in fully dynamic graphs HK Thakur, A Gupta, S Nag, R Shrivastava International Journal of Computational Science and Engineering 21 (1), 69-83, 2020 | 6 | 2020 |
| ITERALIGN: Iterative constitutional alignment of large language models X Chen, H Wen, S Nag, C Luo, Q Yin, R Li, Z Li, W Wang arXiv preprint arXiv:2403.18341, 2024 | 4 | 2024 |
| Supervised contextual embeddings for transfer learning in natural language processing tasks M Kale, A Siddhant, S Nag, R Parik, M Grabmair, A Tomasic arXiv preprint arXiv:1906.12039, 2019 | 4 | 2019 |
| A randomized controlled trial on the efficacy of intravenous magnesium therapy in perinatal asphyxia in a resource-poor setting PKV Kumar, R BilasRanjan, S Nag J Dent Med Sci 14 (3), 5-9, 2015 | 4 | 2015 |
| Simrag: Self-improving retrieval-augmented generation for adapting large language models to specialized domains R Xu, H Liu, S Nag, Z Dai, Y Xie, X Tang, C Luo, Y Li, JC Ho, C Yang, ... arXiv preprint arXiv:2410.17952, 2024 | 2 | 2024 |
| Hierarchical Query Classification in E-commerce Search B He, S Nag, L Cui, S Wang, Z Li, R Goutam, Z Li, H Zhang Companion Proceedings of the ACM on Web Conference 2024, 338-345, 2024 | 1 | 2024 |
| Improving consistency for text summarization with energy functions Q Zeng, Q Yin, Z Li, Y Gao, S Nag, Z Wang, B Yin, H Ji, C Zhang Findings of the Association for Computational Linguistics: EMNLP 2023, 11925 …, 2023 | 1 | 2023 |
| Query Brand Entity Linking in E-Commerce Search D Liu, S Nag arXiv preprint arXiv:2502.01555, 2025 | | 2025 |
| Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning H Han, Y Xie, H Liu, X Tang, S Nag, W Headden, Y Li, C Luo, S Ji, Q He, ... arXiv preprint arXiv:2501.07845, 2025 | | 2025 |
| Exploring Query Understanding for Amazon Product Search C Luo, X Tang, H Lu, Y Xie, H Liu, Z Dai, L Cui, A Joshi, S Nag, Y Li, Z Li, ... 2024 IEEE International Conference on Big Data (BigData), 2343-2348, 2024 | | 2024 |
| Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data J Li, S Nag, H Liu, X Tang, S Sarwar, L Cui, H Gu, S Wang, Q He, J Tang arXiv preprint arXiv:2411.08028, 2024 | | 2024 |
| REAPER: Reasoning based retrieval planning for complex RAG systems A Joshi, SM Sarwar, S Varshney, S Nag, S Agrawal, J Naik Proceedings of the 33rd ACM International Conference on Information and …, 2024 | | 2024 |
| Situated Natural Language Explanations Z Zhu, H Jiang, J Yang, S Nag, C Zhang, J Huang, Y Gao, F Rudzicz, ... arXiv preprint arXiv:2308.14115, 2023 | | 2023 |
| Robust Watermarking for Diffusion Models: A Unified Multi-Dimensional Recipe T Wei, R Qiu, Y Chen, Y Qi, J Lin, W Xu, S Nag, R Li, H Lu, Z Wang, H Liu, ... | | |
| Multi-Class Instance-Incremental Framework for Classification in Fully Dynamic Graphs R Shrivastava, S Nag, HK Thakur, A Gupta | | |
