| How much is my car worth? A methodology for predicting used cars’ prices using random forest N Pal, P Arora, P Kohli, D Sundararaman, SS Palakurthy Advances in Information and Communication Networks: Proceedings of the 2018 …, 2019 | 87 | 2019 |
| Methods for Numeracy-Preserving Word Embeddings D Sundararaman, S Si, V Subramanian, G Wang, D Hazarika, L Carin Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 54 | 2020 |
| Learning compressed sentence representations for on-device text processing D Shen, P Cheng, D Sundararaman, X Zhang, Q Yang, M Tang, ... Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 32 | 2019 |
| Syntax-infused transformer and bert models for machine translation and natural language understanding D Sundararaman, V Subramanian, G Wang, S Si, D Shen, D Wang, ... arXiv preprint arXiv:1911.06156, 2019 | 31 | 2019 |
| Shijing Si, Dinghan Shen, Dong Wang, and Lawrence Carin. 2019. Syntax-infused transformer and bert models for machine translation and natural language understanding D Sundararaman, V Subramanian arXiv preprint arXiv:1911.06156, 2019 | 21 | 2019 |
| Digital Nations–Smart Cities, Innovation, and Sustainability: 16th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2017, Delhi, India, November 21–23 … AK Kar, PV Ilavarasan, MP Gupta, YK Dwivedi, M Mäntymäki, M Janssen, ... Springer, 2017 | 14 | 2017 |
| Shijing Si, Dinghan Shen, Dong Wang, and Lawrence Carin. Syntax-infused transformer and bert models for machine translation and natural language understanding D Sundararaman, V Subramanian arXiv preprint arXiv:1911.06156, 2019 | 13 | 2019 |
| Syntactic Knowledge-Infused Transformer and BERT Models. D Sundararaman, V Subramanian, G Wang, S Si, D Shen, D Wang, ... CIKM Workshops, 2021 | 12 | 2021 |
| Improving Downstream Task Performance by Treating Numbers as Entities D Sundararaman, V Subramanian, G Wang, L Xu, L Carin Proceedings of the 31st ACM International Conference on Information …, 2022 | 8* | 2022 |
| What BERT Based Language Models Learn in Spoken Transcripts: An Empirical Study A Kumar, MN Sundararaman, J Vepa arXiv preprint arXiv:2109.09105, 2021 | 7 | 2021 |
| How do lexical semantics affect translation? An empirical study V Subramanian, D Sundararaman arXiv preprint arXiv:2201.00075, 2021 | 6 | 2021 |
| Implementing MLOps in the Enterprise Y Haviv, N Gift " O'Reilly Media, Inc.", 2023 | 5 | 2023 |
| Exploring Gender Bias in Retrieval Models D Sundararaman, V Subramanian arXiv preprint arXiv:2208.01755, 2022 | 5* | 2022 |
| Twigraph: discovering and visualizing influential words between Twitter profiles D Sundararaman, S Srinivasan Social Informatics: 9th International Conference, SocInfo 2017, Oxford, UK …, 2017 | 5 | 2017 |
| Syntax-infused transformer and BERT models for machine translation and natural language understanding S Dhanasekar, S Vivek, W Guoyin, S Shijing, S Dinghan, W Dong, ... arXiv preprint arXiv: 1911. 06156v1, 2019 | 3 | 2019 |
| Customizable Vehicle Tracking with Intelligent Prediction System D Sundararaman, G Ravichandran, R Jagadeesh, S Sasirekha, ... Conference on e-Business, e-Services and e-Society, 298-310, 2017 | 3 | 2017 |
| An analysis of nonimmigrant work visas in the USA using Machine Learning D Sundararaman, N Pal, AK Misraa Int. J. Comput. Sci. Secur.(IJCSS) 6, 2017 | 3 | 2017 |
| Learning Task Sampling Policy for Multitask Learning D Sundararaman, H Tsai, KH Lee, I Turc, L Carin Findings of the Association for Computational Linguistics: EMNLP 2021, 4410-4415, 2021 | 2 | 2021 |
| Evaluating Hallucination in Large Vision-Language Models based on Context-Aware Object Similarities S Datta, D Sundararaman arXiv preprint arXiv:2501.15046, 2025 | | 2025 |
| Pseudo-OOD training for robust language models D Sundararaman, N Mehta, L Carin arXiv preprint arXiv:2210.09132, 2022 | | 2022 |
Vivek SubramanianAmazon, Inc.Verified email at amazon.com