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Albert Webson
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Year
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
15592022
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
12232022
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
11572022
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
4672023
Crosslingual Generalization through Multitask Finetuning
N Muennighoff, T Wang, L Sutawika, A Roberts, S Biderman, TL Scao, ...
arXiv preprint arXiv:2211.01786, 2022
3702022
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
3342023
Do Prompt-Based Models Really Understand the Meaning of their Prompts?
A Webson, E Pavlick
arXiv preprint arXiv:2109.01247, 2021
2562021
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
2392022
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
1562023
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
1062022
Towards conversational diagnostic AI
T Tu, A Palepu, M Schaekermann, K Saab, J Freyberg, R Tanno, A Wang, ...
arXiv preprint arXiv:2401.05654, 2024
282024
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
20*2020
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
192023
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
182023
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
92023
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
92023
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
82024
Evaluating Frontier Models for Dangerous Capabilities
M Phuong, M Aitchison, E Catt, S Cogan, A Kaskasoli, V Krakovna, ...
arXiv preprint arXiv:2403.13793, 2024
12024
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
12023
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