| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... ArXiv Preprint, 2023 | 3479* | 2023 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... ArXiv Preprint, 2022 | 1553* | 2022 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... ArXiv Preprint, 2024 | 1220* | 2024 |
| Looking beyond the surface: A challenge set for reading comprehension over multiple sentences D Khashabi, S Chaturvedi, M Roth, S Upadhyay, D Roth NAACL 2018 (Long Paper), 2018 | 562 | 2018 |
| Attention Interpretability across NLP Tasks S Vashishth, S Upadhyay, GS Tomar, M Faruqui ArXiv Preprint, 2019 | 251* | 2019 |
| Cross-lingual models of word embeddings: An empirical comparison S Upadhyay, M Faruqui, C Dyer, D Roth ACL 2016 (Long Paper), 2016 | 223 | 2016 |
| Tableformer: Robust transformer modeling for table-text encoding J Yang, A Gupta, S Upadhyay, L He, R Goel, S Paul ACL 2022 (Long Paper), 2022 | 116 | 2022 |
| Gemini: a family of highly capable multimodal models. arXiv. org G Team, R Anil, S Borgeaud, J Alayrac, J Yu, R Soricut, J Schalkwyk, ... | 92* | 2023 |
| TIMEDIAL: Temporal commonsense reasoning in dialog L Qin, A Gupta, S Upadhyay, L He, Y Choi, M Faruqui ACL 2021 (Long Paper), 2021 | 71 | 2021 |
| Annotating derivations: A new evaluation strategy and dataset for algebra word problems S Upadhyay, MW Chang EACL 2017 (Long Paper), 2017 | 68 | 2017 |
| How FaR Are Large Language Models From Agents with Theory-of-Mind? P Zhou, A Madaan, SP Potharaju, A Gupta, KR McKee, A Holtzman, ... ArXiv Preprint, 2023 | 63 | 2023 |
| Learning from explicit and implicit supervision jointly for algebra word problems S Upadhyay, MW Chang, KW Chang, W Yih EMNLP 2016 (Long Paper), 2016 | 60 | 2016 |
| Joint multilingual supervision for cross-lingual entity linking S Upadhyay, N Gupta, D Roth EMNLP 2018 (Long Paper), 2018 | 50 | 2018 |
| Equation parsing: Mapping sentences to grounded equations S Roy, S Upadhyay, D Roth EMNLP 2016 (Long Paper), 2016 | 40 | 2016 |
| Cogcompnlp: Your swiss army knife for nlp D Khashabi, M Sammons, B Zhou, T Redman, C Christodoulopoulos, ... LREC 2018, 2018 | 38* | 2018 |
| Beyond bilingual: Multi-sense word embeddings using multilingual context S Upadhyay, KW Chang, M Taddy, A Kalai, J Zou Repl4NLP Workshop 2017 (Best Paper Award), 2017 | 34 | 2017 |
| Disfl-QA: A benchmark dataset for understanding disfluencies in question answering A Gupta, J Xu, S Upadhyay, D Yang, M Faruqui Findings of ACL-IJCNLP 2021, 2021 | 31 | 2021 |
| Automix: Automatically mixing language models A Madaan, P Aggarwal, A Anand, SP Potharaju, S Mishra, P Zhou, ... NeurIPS 2024, 2024 | 30* | 2024 |
| (Almost) zero-shot cross-lingual spoken language understanding S Upadhyay, M Faruqui, G Tür, HT Dilek, L Heck ICASSP 2018, 2018 | 28 | 2018 |
| Robust cross-lingual hypernymy detection using dependency context S Upadhyay, Y Vyas, M Carpuat, D Roth NAACL 2018 (Long Paper), 2018 | 26 | 2018 |
Dan RothProfessor of Computer Science, University of PennsylvaniaE-mailová adresa ověřena na: seas.upenn.edu