| How multilingual is Multilingual BERT? T Pires, E Schlinger, D Garrette Proceedings of ACL, 2019 | 1603 | 2019 |
| Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 1548 | 2023 |
| BLOOM: A 176B-Parameter Open-Access Multilingual Language Model TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ... arXiv preprint arXiv:2211.05100, 2022 | 1499 | 2022 |
| 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 arXiv:2206.04615, 2022 | 1017 | 2022 |
| TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages JH Clark, E Choi, M Collins, D Garrette, T Kwiatkowski, V Nikolaev, ... Transactions of the Association for Computational Linguistics 8, 454-470, 2020 | 519 | 2020 |
| Dynet: The dynamic neural network toolkit G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ... arXiv preprint arXiv:1701.03980, 2017 | 275 | 2017 |
| Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation JH Clark, D Garrette, I Turc, J Wieting Transactions of the Association for Computational Linguistics 10, 73-91, 2022 | 198 | 2022 |
| Scaling up models and data with t5x and seqio A Roberts, HW Chung, G Mishra, A Levskaya, J Bradbury, D Andor, ... Journal of Machine Learning Research 24 (377), 1-8, 2023 | 143 | 2023 |
| XTREME-R: Towards more challenging and nuanced multilingual evaluation S Ruder, N Constant, J Botha, A Siddhant, O Firat, J Fu, P Liu, J Hu, ... EMNLP, 2021 | 140 | 2021 |
| Learning a Part-of-Speech Tagger from Two Hours of Annotation D Garrette, J Baldridge Proceedings of NAACL, 2013 | 132 | 2013 |
| Montague Meets Markov: Deep Semantics with Probabilistic Logical Form I Beltagy, C Chau, G Boleda, D Garrette, K Erk, R Mooney Proceedings of *SEM, 2013 | 111 | 2013 |
| Integrating logical representations with probabilistic information using Markov logic D Garrette, K Erk, R Mooney Proceedings of the International Conference on Computational Semantics, 2011 | 75 | 2011 |
| Frequency effects on syntactic rule learning in transformers J Wei, D Garrette, T Linzen, E Pavlick arXiv preprint arXiv:2109.07020, 2021 | 63 | 2021 |
| Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages D Garrette, J Mielens, J Baldridge Proceedings of ACL, 2013 | 61 | 2013 |
| Improving Multilingual Models with Language-Clustered Vocabularies HW Chung, D Garrette, KC Tan, J Riesa Proceedings of EMNLP, 2020 | 58 | 2020 |
| Character-aware models improve visual text rendering R Liu, D Garrette, C Saharia, W Chan, A Roberts, S Narang, I Blok, ... arXiv preprint arXiv:2212.10562, 2022 | 43 | 2022 |
| A formal approach to linking logical form and vector-space lexical semantics D Garrette, K Erk, R Mooney Computing Meaning 4, 2013 | 37 | 2013 |
| Type-Supervised Hidden Markov Models for Part-of-Speech Tagging with Incomplete Tag Dictionaries D Garrette, J Baldridge Proceedings of EMNLP, 2012 | 32 | 2012 |
| Part-of-Speech Tagging for Code-Switched, Transliterated Texts without Explicit Language Identification K Ball, D Garrette Proceedings of EMNLP, 2018 | 30 | 2018 |
| An extensible toolkit for computational semantics D Garrette, E Klein Proceedings of the International Conference on Computational Semantics, 2009 | 27 | 2009 |
Jason BaldridgeResearch Scientist, GoogleVerified email at google.com
