| Scaling Instruction-Finetuned Language Models HW Chung, L Hou, S Longpre, B Zoph, Y Tay, W Fedus, E Li, X Wang, ... arXiv preprint arXiv:2210.11416, 2022 | 3296 | 2022 |
| 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 | 2517 | 2023 |
| Multitask Prompted Training Enables Zero-Shot Task Generalization V Sanh, A Webson, C Raffel, SH Bach, L Sutawika, Z Alyafeai, A Chaffin, ... International Conference on Learning Representations, 2022 | 1772 | 2022 |
| 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 | 1757 | 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 arXiv:2403.05530, 2024 | 963 | 2024 |
| Crosslingual Generalization through Multitask Finetuning N Muennighoff, T Wang, L Sutawika, A Roberts, S Biderman, TL Scao, ... arXiv preprint arXiv:2211.01786, 2022 | 686 | 2022 |
| The Flan Collection: Designing Data and Methods for Effective Instruction Tuning S Longpre, L Hou, T Vu, A Webson, HW Chung, Y Tay, D Zhou, QV Le, ... arXiv preprint arXiv:2301.13688, 2023 | 669 | 2023 |
| Do Prompt-Based Models Really Understand the Meaning of their Prompts? A Webson, E Pavlick arXiv preprint arXiv:2109.01247, 2021 | 387 | 2021 |
| PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts SH Bach, V Sanh, ZX Yong, A Webson, C Raffel, NV Nayak, A Sharma, ... arXiv preprint arXiv:2202.01279, 2022 | 329 | 2022 |
| Larger language models do in-context learning differently J Wei, J Wei, Y Tay, D Tran, A Webson, Y Lu, X Chen, H Liu, D Huang, ... arXiv preprint arXiv:2303.03846, 2023 | 305 | 2023 |
| Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models H Strobelt, A Webson, V Sanh, B Hoover, J Beyer, H Pfister, AM Rush IEEE transactions on visualization and computer graphics 29 (1), 1146-1156, 2022 | 198 | 2022 |
| Towards conversational diagnostic AI T Tu, A Palepu, M Schaekermann, K Saab, J Freyberg, R Tanno, A Wang, ... arXiv preprint arXiv:2401.05654, 2024 | 151 | 2024 |
| Capabilities of gemini models in medicine K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ... arXiv preprint arXiv:2404.18416, 2024 | 133 | 2024 |
| Mixture-of-experts meets instruction tuning: A winning combination for large language models S Shen, L Hou, Y Zhou, N Du, S Longpre, J Wei, HW Chung, B Zoph, ... arXiv preprint arXiv:2305.14705, 2023 | 67 | 2023 |
| Evaluating Frontier Models for Dangerous Capabilities M Phuong, M Aitchison, E Catt, S Cogan, A Kaskasoli, V Krakovna, ... arXiv preprint arXiv:2403.13793, 2024 | 46 | 2024 |
| Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts S Shen, L Hou, Y Zhou, N Du, S Longpre, J Wei, HW Chung, B Zoph, ... arXiv preprint arXiv:2305.14705, 2023 | 30 | 2023 |
| Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs K Guu, A Webson, E Pavlick, L Dixon, I Tenney, T Bolukbasi arXiv preprint arXiv:2303.08114, 2023 | 28 | 2023 |
| Are “Undocumented Immigrants” the Same as “Illegal Aliens”? Differentiating Denotation and Connotation in Vector Spaces A Webson, Z Chen, C Eickhoff, E Pavlick Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 25* | 2020 |
| Are Language Models Worse than Humans at Following Prompts? It's Complicated A Webson, AM Loo, Q Yu, E Pavlick arXiv preprint arXiv:2301.07085, 2023 | 13 | 2023 |
| In-context learning generalizes, but not always robustly: The case of syntax A Mueller, A Webson, J Petty, T Linzen arXiv preprint arXiv:2311.07811, 2023 | 7 | 2023 |
Ellie PavlickBrown UniversityVerified email at brown.edu