Nikola Momchev
Nikola Momchev
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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
Measuring compositional generalization: A comprehensive method on realistic data
D Keysers, N Schärli, N Scales, H Buisman, D Furrer, S Kashubin, ...
arXiv preprint arXiv:1912.09713, 2019
Acme: A research framework for distributed reinforcement learning
MW Hoffman, B Shahriari, J Aslanides, G Barth-Maron, N Momchev, ...
arXiv preprint arXiv:2006.00979, 2020
Nash learning from human feedback
R Munos, M Valko, D Calandriello, MG Azar, M Rowland, ZD Guo, Y Tang, ...
arXiv preprint arXiv:2312.00886, 2023
Factually consistent summarization via reinforcement learning with textual entailment feedback
P Roit, J Ferret, L Shani, R Aharoni, G Cideron, R Dadashi, M Geist, ...
arXiv preprint arXiv:2306.00186, 2023
Hyperparameter selection for imitation learning
L Hussenot, M Andrychowicz, D Vincent, R Dadashi, A Raichuk, S Ramos, ...
International Conference on Machine Learning, 4511-4522, 2021
*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task
D Tsarkov, T Tihon, N Scales, N Momchev, D Sinopalnikov, N Schärli
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9949-9957, 2021
Rlds: an ecosystem to generate, share and use datasets in reinforcement learning
S Ramos, S Girgin, L Hussenot, D Vincent, H Yakubovich, D Toyama, ...
arXiv preprint arXiv:2111.02767, 2021
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