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Dani Yogatama
Dani Yogatama
Reka, USC
Adresă de e-mail confirmată pe reka.ai - Pagina de pornire
Titlu
Citat de
Citat de
Anul
Grandmaster level in StarCraft II using multi-agent reinforcement learning
O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ...
nature 575 (7782), 350-354, 2019
51672019
Deep speech 2: End-to-end speech recognition in english and mandarin
D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ...
International conference on machine learning, 173-182, 2016
39472016
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
3543*2022
Part-of-speech tagging for twitter: Annotation, features, and experiments
K Gimpel, N Schneider, B O’connor, D Das, DP Mills, J Eisenstein, ...
Proceedings of the 49th annual meeting of the Association for Computational …, 2011
13482011
On the cross-lingual transferability of monolingual representations
M Artetxe, S Ruder, D Yogatama
arXiv preprint arXiv:1910.11856, 2019
7952019
Program induction by rationale generation: Learning to solve and explain algebraic word problems
W Ling, D Yogatama, C Dyer, P Blunsom
arXiv preprint arXiv:1705.04146, 2017
6712017
AlphaStar: Mastering the Real-Time Strategy Game StarCraft II
O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, W Czarnecki, ...
5832019
Random feature attention
H Peng, N Pappas, D Yogatama, R Schwartz, NA Smith, L Kong
arXiv preprint arXiv:2103.02143, 2021
3842021
Generative and discriminative text classification with recurrent neural networks
D Yogatama, C Dyer, W Ling, P Blunsom
arXiv preprint arXiv:1703.01898, 2017
2732017
Efficient Transfer Learning Method for Automatic Hyperparameter Tuning
D Yogatama, G Mann
Proceedings of the 17th International Conference on Artificial Intelligence …, 2014
2702014
Episodic memory in lifelong language learning
C de Masson D'Autume, S Ruder, L Kong, D Yogatama
Advances in Neural Information Processing Systems 32, 2019
2532019
Sparse overcomplete word vector representations
M Faruqui, Y Tsvetkov, D Yogatama, C Dyer, N Smith
ACL 2015, 2015
2522015
A contrastive framework for neural text generation
Y Su, T Lan, Y Wang, D Yogatama, L Kong, N Collier
Advances in Neural Information Processing Systems 35, 21548-21561, 2022
2232022
Learning and evaluating general linguistic intelligence
D Yogatama, CM d'Autume, J Connor, T Kocisky, M Chrzanowski, L Kong, ...
arXiv preprint arXiv:1901.11373, 2019
222*2019
Reducing sentiment bias in language models via counterfactual evaluation
PS Huang, H Zhang, R Jiang, R Stanforth, J Welbl, J Rae, V Maini, ...
arXiv preprint arXiv:1911.03064, 2019
2162019
Learning to compose words into sentences with reinforcement learning
D Yogatama, P Blunsom, C Dyer, E Grefenstette, W Ling
arXiv preprint arXiv:1611.09100, 2016
2102016
Mind the gap: Assessing temporal generalization in neural language models
A Lazaridou, A Kuncoro, E Gribovskaya, D Agrawal, A Liska, T Terzi, ...
Advances in Neural Information Processing Systems 34, 29348-29363, 2021
198*2021
Achieving verified robustness to symbol substitutions via interval bound propagation
PS Huang, R Stanforth, J Welbl, C Dyer, D Yogatama, S Gowal, ...
arXiv preprint arXiv:1909.01492, 2019
1882019
Emergent abilities of large language models. arXiv
J Wei, Y Tay, R Bommasani, C Raffel, B Zoph, S Borgeaud, D Yogatama, ...
arXiv preprint arXiv:2206.07682 10, 2022
1722022
LSTMs can learn syntax-sensitive dependencies well, but modeling structure makes them better
A Kuncoro, C Dyer, J Hale, D Yogatama, S Clark, P Blunsom
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
1722018
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