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Acyr Locatelli
Acyr Locatelli
Cohere
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Pushing mixture of experts to the limit: Extremely parameter efficient moe for instruction tuning
T Zadouri, A Üstün, A Ahmadian, B Ermiş, A Locatelli, S Hooker
arXiv preprint arXiv:2309.05444, 2023
522023
Aya 23: Open weight releases to further multilingual progress
V Aryabumi, J Dang, D Talupuru, S Dash, D Cairuz, H Lin, B Venkitesh, ...
arXiv preprint arXiv:2405.15032, 2024
172024
Exploring low rank training of deep neural networks
SR Kamalakara, A Locatelli, B Venkitesh, J Ba, Y Gal, AN Gomez
arXiv preprint arXiv:2209.13569, 2022
132022
Snapkv: Llm knows what you are looking for before generation
Y Li, Y Huang, B Yang, B Venkitesh, A Locatelli, H Ye, T Cai, P Lewis, ...
arXiv preprint arXiv:2404.14469, 2024
122024
Regular cylindrical algebraic decomposition
JH Davenport, AF Locatelli, GK Sankaran
Journal of the London Mathematical Society 101 (1), 43-59, 2020
42020
On the regularity of cylindrical algebraic decompositions
A Locatelli
University of Bath, 2015
22015
To Code, or Not To Code? Exploring Impact of Code in Pre-training
V Aryabumi, Y Su, R Ma, A Morisot, I Zhang, A Locatelli, M Fadaee, ...
arXiv preprint arXiv:2408.10914, 2024
2024
BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts
Q Zhang, N Gritsch, D Gnaneshwar, S Guo, D Cairuz, B Venkitesh, ...
arXiv preprint arXiv:2408.08274, 2024
2024
System and Method for Low Rank Training of Neural Networks
SR Kamalakara, B Venkitesh, AN Gomez, AFN Locatelli
US Patent App. 17/814,041, 2023
2023
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