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Sebastian Borgeaud
Sebastian Borgeaud
DeepMind
Bestätigte E-Mail-Adresse bei google.com
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Zitiert von
Zitiert von
Jahr
Flamingo: a visual language model for few-shot learning
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
Advances in neural information processing systems 35, 23716-23736, 2022
37342022
Emergent abilities of large language models
J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ...
arXiv preprint arXiv:2206.07682, 2022
3353*2022
Training compute-optimal large language models
J Hoffmann, S Borgeaud, A Mensch, E Buchatskaya, T Cai, E Rutherford, ...
arXiv preprint arXiv:2203.15556, 2022
2551*2022
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
24642023
Scaling language models: Methods, analysis & insights from training gopher
JW Rae, S Borgeaud, T Cai, K Millican, J Hoffmann, F Song, J Aslanides, ...
arXiv preprint arXiv:2112.11446, 2021
1301*2021
Improving language models by retrieving from trillions of tokens
S Borgeaud, A Mensch, J Hoffmann, T Cai, E Rutherford, K Millican, ...
arXiv preprint arXiv:2112.04426, 2021
10982021
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ...
arXiv preprint arXiv:2403.05530, 2024
9722024
Gemma: Open models based on gemini research and technology
G Team, T Mesnard, C Hardin, R Dadashi, S Bhupatiraju, S Pathak, ...
arXiv preprint arXiv:2403.08295, 2024
9092024
Perceiver io: A general architecture for structured inputs & outputs
A Jaegle, S Borgeaud, JB Alayrac, C Doersch, C Ionescu, D Ding, ...
arXiv preprint arXiv:2107.14795, 2021
6252021
OpenSpiel: A framework for reinforcement learning in games
M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint arXiv:1908.09453, 2019
3272019
Gemma 2: Improving open language models at a practical size
G Team, M Riviere, S Pathak, PG Sessa, C Hardin, S Bhupatiraju, ...
arXiv preprint arXiv:2408.00118, 2024
3102024
Gemini: A family of highly capable multimodal models
R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805 1, 2023
3022023
Accelerating large language model decoding with speculative sampling
C Chen, S Borgeaud, G Irving, JB Lespiau, L Sifre, J Jumper
arXiv preprint arXiv:2302.01318, 2023
2862023
others. 2023. Gemini: a family of highly capable multimodal models
RA Gemini Team, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 0
231
Unsupervised learning of object keypoints for perception and control
TD Kulkarni, A Gupta, C Ionescu, S Borgeaud, M Reynolds, A Zisserman, ...
Advances in neural information processing systems 32, 2019
2252019
Mikoł aj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karén Simonyan. Flamingo: a visual language model for few-shot learning
JB Alayrac, J Donahue, P Luc, A Miech, I Barr, Y Hasson, K Lenc, ...
Advances in Neural Information Processing Systems 35, 23716-23736, 2022
902022
General-purpose, long-context autoregressive modeling with Perceiver AR
C Hawthorne, A Jaegle, C Cangea, S Borgeaud, C Nash, M Malinowski, ...
International Conference on Machine Learning, 8535-8558, 2022
682022
Emergent abilities of large language models. arXiv 2022
J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ...
arXiv preprint arXiv:2206.07682, 2023
672023
Unified scaling laws for routed language models
A Clark, D de Las Casas, A Guy, A Mensch, M Paganini, J Hoffmann, ...
International conference on machine learning, 4057-4086, 2022
632022
Spriteworld: A flexible, configurable reinforcement learning environment
N Watters, L Matthey, S Borgeaud, R Kabra, A Lerchner
202019
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