| Moving down the long tail of word sense disambiguation with gloss-informed biencoders T Blevins, L Zettlemoyer arXiv preprint arXiv:2005.02590, 2020 | 177 | 2020 |
| Detecting pretraining data from large language models W Shi, A Ajith, M Xia, Y Huang, D Liu, T Blevins, D Chen, L Zettlemoyer arXiv preprint arXiv:2310.16789, 2023 | 173 | 2023 |
| Demystifying prompts in language models via perplexity estimation H Gonen, S Iyer, T Blevins, NA Smith, L Zettlemoyer arXiv preprint arXiv:2212.04037, 2022 | 144 | 2022 |
| Deep RNNs encode soft hierarchical syntax T Blevins, O Levy, L Zettlemoyer arXiv preprint arXiv:1805.04218, 2018 | 137 | 2018 |
| Automatically processing tweets from gang-involved youth: towards detecting loss and aggression T Blevins, R Kwiatkowski, JC Macbeth, K McKeown, D Patton, O Rambow | 55 | 2016 |
| Language contamination helps explain the cross-lingual capabilities of English pretrained models T Blevins, L Zettlemoyer arXiv preprint arXiv:2204.08110, 2022 | 54 | 2022 |
| Prompting language models for linguistic structure T Blevins, H Gonen, L Zettlemoyer arXiv preprint arXiv:2211.07830, 2022 | 25 | 2022 |
| Analyzing the mono-and cross-lingual pretraining dynamics of multilingual language models T Blevins, H Gonen, L Zettlemoyer arXiv preprint arXiv:2205.11758, 2022 | 24 | 2022 |
| FEWS: Large-scale, low-shot word sense disambiguation with the dictionary T Blevins, M Joshi, L Zettlemoyer arXiv preprint arXiv:2102.07983, 2021 | 24 | 2021 |
| Breaking the curse of multilinguality with cross-lingual expert language models T Blevins, T Limisiewicz, S Gururangan, M Li, H Gonen, NA Smith, ... arXiv preprint arXiv:2401.10440, 2024 | 14 | 2024 |
| Buffet: Benchmarking large language models for few-shot cross-lingual transfer A Asai, S Kudugunta, XV Yu, T Blevins, H Gonen, M Reid, Y Tsvetkov, ... arXiv preprint arXiv:2305.14857, 2023 | 11 | 2023 |
| Better character language modeling through morphology T Blevins, L Zettlemoyer arXiv preprint arXiv:1906.01037, 2019 | 10 | 2019 |
| Mining paraphrasal typed templates from a plain text corpus O Biran, T Blevins, K McKeown Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016 | 9 | 2016 |
| Nanoscience of metal silicate-based pigments TT Salguero, D Johnson-McDaniel, CA Barrett, A Sharafi, R Weimar, ... MRS Online Proceedings Library (OPL) 1618, 161-166, 2014 | 9 | 2014 |
| Myte: Morphology-driven byte encoding for better and fairer multilingual language modeling T Limisiewicz, T Blevins, H Gonen, O Ahia, L Zettlemoyer arXiv preprint arXiv:2403.10691, 2024 | 8 | 2024 |
| Embedding structure matters: Comparing methods to adapt multilingual vocabularies to new languages CM Downey, T Blevins, N Goldfine, S Steinert-Threlkeld arXiv preprint arXiv:2309.04679, 2023 | 7 | 2023 |
| Comparing hallucination detection metrics for multilingual generation H Kang, T Blevins, L Zettlemoyer arXiv preprint arXiv:2402.10496, 2024 | 6 | 2024 |
| Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmark S Mayhew, T Blevins, S Liu, M Šuppa, H Gonen, JM Imperial, BF Karlsson, ... arXiv preprint arXiv:2311.09122, 2023 | 5 | 2023 |
| Translate to disambiguate: Zero-shot multilingual word sense disambiguation with pretrained language models H Kang, T Blevins, L Zettlemoyer arXiv preprint arXiv:2304.13803, 2023 | 4 | 2023 |
| Targeted Multilingual Adaptation for Low-resource Language Families CM Downey, T Blevins, D Serai, D Parikh, S Steinert-Threlkeld arXiv preprint arXiv:2405.12413, 2024 | 2 | 2024 |
