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Angeliki Lazaridou
Angeliki Lazaridou
Research Scientist, Google DeepMind
E-mail confirmado em google.com - Página inicial
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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
842*2021
A unified game-theoretic approach to multiagent reinforcement learning
M Lanctot, V Zambaldi, A Gruslys, A Lazaridou, K Tuyls, J Pérolat, D Silver, ...
Advances in neural information processing systems 30, 2017
6982017
Social influence as intrinsic motivation for multi-agent deep reinforcement learning
N Jaques, A Lazaridou, E Hughes, C Gulcehre, P Ortega, DJ Strouse, ...
International conference on machine learning, 3040-3049, 2019
495*2019
Multi-agent cooperation and the emergence of (natural) language
A Lazaridou, A Peysakhovich, M Baroni
arXiv preprint arXiv:1612.07182, 2016
4902016
Improving zero-shot learning by mitigating the hubness problem
G Dinu, A Lazaridou, M Baroni
ICLR, Workshop Track, 2015
4412015
The LAMBADA dataset: Word prediction requiring a broad discourse context
D Paperno, G Kruszewski, A Lazaridou, QN Pham, R Bernardi, S Pezzelle, ...
arXiv preprint arXiv:1606.06031, 2016
3742016
Experience grounds language
Y Bisk, A Holtzman, J Thomason, J Andreas, Y Bengio, J Chai, M Lapata, ...
arXiv preprint arXiv:2004.10151, 2020
3542020
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
3482023
Combining Language and Vision with a Multimodal Skip-gram Model
A Lazaridou, NT Pham, M Baroni
NAACL, 2015
3442015
Hubness and Pollution: Delving into Cross-Space Mapping for Zero-Shot Learning
A Lazaridou, G Dinu, M Baroni
Proceedings of ACL 1, 270--280, 2015
2532015
Emergence of linguistic communication from referential games with symbolic and pixel input
A Lazaridou, KM Hermann, K Tuyls, S Clark
arXiv preprint arXiv:1804.03984, 2018
2302018
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
206*2019
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
184*2021
Emergent communication through negotiation
K Cao, A Lazaridou, M Lanctot, JZ Leibo, K Tuyls, S Clark
arXiv preprint arXiv:1804.03980, 2018
1782018
Emergent multi-agent communication in the deep learning era
A Lazaridou, M Baroni
arXiv preprint arXiv:2006.02419, 2020
1662020
Is this a wampimuk? cross-modal mapping between distributional semantics and the visual world
A Lazaridou, E Bruni, M Baroni
Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014
1472014
Compositional-ly Derived Representations of Morphologically Complex Words in Distributional Semantics
A Lazaridou, M Marelli, R Zamparelli, M Baroni
Proceedings of ACL, Sofia, Bulgaria, 2013
1432013
Internet-augmented language models through few-shot prompting for open-domain question answering
A Lazaridou, E Gribovskaya, W Stokowiec, N Grigorev
arXiv preprint arXiv:2203.05115, 2022
1412022
The repeval 2017 shared task: Multi-genre natural language inference with sentence representations
N Nangia, A Williams, A Lazaridou, SR Bowman
arXiv preprint arXiv:1707.08172, 2017
1082017
Compositional obverter communication learning from raw visual input
E Choi, A Lazaridou, N De Freitas
arXiv preprint arXiv:1804.02341, 2018
100*2018
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Artigos 1–20