| Systematic review of effect of data augmentation using paraphrasing on named entity recognition S Sharma, A Joshi, N Mukhija, Y Zhao, H Bhathena, P Singh, ... NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research, 2022 | 8 | 2022 |
| Evaluating compositionality of sentence representation models H Bhathena, A Willis, N Dass Proceedings of the 5th Workshop on Representation Learning for NLP, 185-193, 2020 | 5 | 2020 |
| When and how to paraphrase for named entity recognition? S Sharma, A Joshi, Y Zhao, N Mukhija, H Bhathena, P Singh, ... Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 2 | 2023 |
| Recognizing themes in Amazon reviews through Unsupervised Multi-Document Summarization H Bhathena, J Chen, W Locke | 1 | |
| [Industry] An efficient method for Natural Language Querying on Structured Data H Bhathena, A Joshi, P Singh The 61st Annual Meeting Of The Association For Computational Linguistics, 2023 | | 2023 |
| An efficient method for Natural Language Querying on Structured Data H Bhathena, A Joshi, P Singh Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | | 2023 |
| Quantifying and Evaluating Positive Transfer using Multi-task Learning for NLP H Bhathena, D Salz, S Shakeri | | 2019 |
| Deep Transfer Learning for NLP on Small Data Sets H Bhathena Nvidia GTC 2019, 2019 | | 2019 |
Nathan DassGoogle ResearchVerified email at google.com
Nathan DassGoogle ResearchVerified email at google.com