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Roberta Raileanu
Roberta Raileanu
Research Scientist, Meta
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Title
Cited by
Cited by
Year
Toolformer: Language models can teach themselves to use tools
T Schick, J Dwivedi-Yu, R Dessì, R Raileanu, M Lomeli, E Hambro, ...
Advances in Neural Information Processing Systems 36, 2024
8462024
Augmented language models: a survey
G Mialon, R Dessì, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ...
arXiv preprint arXiv:2302.07842, 2023
3402023
Modeling others using oneself in multi-agent reinforcement learning
R Raileanu, E Denton, A Szlam, R Fergus
International conference on machine learning, 4257-4266, 2018
2262018
Challenges and applications of large language models
J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy
arXiv preprint arXiv:2307.10169, 2023
2242023
Ride: Rewarding impact-driven exploration for procedurally-generated environments
R Raileanu, T Rocktäschel
arXiv preprint arXiv:2002.12292, 2020
1832020
Superbubbles in the Multiphase ISM and the Loading of Galactic Winds
CG Kim, EC Ostriker, R Raileanu
The Astrophysical Journal 834 (1), 25, 2016
1702016
The nethack learning environment
H Küttler, N Nardelli, A Miller, R Raileanu, M Selvatici, E Grefenstette, ...
Advances in Neural Information Processing Systems 33, 7671-7684, 2020
1502020
Open-ended learning leads to generally capable agents
OEL Team, A Stooke, A Mahajan, C Barros, C Deck, J Bauer, J Sygnowski, ...
arXiv preprint arXiv:2107.12808, 2021
1492021
Learning with amigo: Adversarially motivated intrinsic goals
A Campero, R Raileanu, H Küttler, JB Tenenbaum, T Rocktäschel, ...
arXiv preprint arXiv:2006.12122, 2020
1402020
Chain-of-verification reduces hallucination in large language models
S Dhuliawala, M Komeili, J Xu, R Raileanu, X Li, A Celikyilmaz, J Weston
arXiv preprint arXiv:2309.11495, 2023
1332023
Automatic data augmentation for generalization in deep reinforcement learning
R Raileanu, M Goldstein, D Yarats, I Kostrikov, R Fergus
arXiv preprint arXiv:2006.12862, 2020
1042020
Automatic data augmentation for generalization in reinforcement learning
R Raileanu, M Goldstein, D Yarats, I Kostrikov, R Fergus
Advances in Neural Information Processing Systems 34, 5402-5415, 2021
962021
Decoupling value and policy for generalization in reinforcement learning
R Raileanu, R Fergus
International Conference on Machine Learning, 8787-8798, 2021
932021
Improving intrinsic exploration with language abstractions
J Mu, V Zhong, R Raileanu, M Jiang, N Goodman, T Rocktäschel, ...
Advances in Neural Information Processing Systems 35, 33947-33960, 2022
492022
Backplay:" man muss immer umkehren"
C Resnick, R Raileanu, S Kapoor, A Peysakhovich, K Cho, J Bruna
arXiv preprint arXiv:1807.06919, 2018
432018
Understanding the effects of rlhf on llm generalisation and diversity
R Kirk, I Mediratta, C Nalmpantis, J Luketina, E Hambro, E Grefenstette, ...
arXiv preprint arXiv:2310.06452, 2023
272023
Exploration via elliptical episodic bonuses
M Henaff, R Raileanu, M Jiang, T Rocktäschel
Advances in Neural Information Processing Systems 35, 37631-37646, 2022
262022
Fast adaptation to new environments via policy-dynamics value functions
R Raileanu, M Goldstein, A Szlam, R Fergus
Proceedings of the 37th International Conference on Machine Learning, 7920-7931, 2020
252020
Building a subspace of policies for scalable continual learning
JB Gaya, T Doan, L Caccia, L Soulier, L Denoyer, R Raileanu
arXiv preprint arXiv:2211.10445, 2022
212022
Toolformer: language models can teach themselves to use tools. 2023
T Schick, J Dwivedi-Yu, R Dessì, R Raileanu, M Lomeli, L Zettlemoyer, ...
arXiv preprint arXiv:2302.04761, 2023
192023
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