Myle Ott
Myle Ott
Facebook AI Research
Verified email at fb.com - Homepage
Title
Cited by
Cited by
Year
Finding deceptive opinion spam by any stretch of the imagination
M Ott, Y Choi, C Cardie, JT Hancock
Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011
10212011
RoBERTa: A robustly optimized BERT pretraining approach
Y Liu, M Ott, N Goyal, J Du, M Joshi, D Chen, O Levy, M Lewis, ...
arXiv preprint arXiv:1907.11692, 2019
270*2019
Estimating the prevalence of deception in online review communities
M Ott, C Cardie, J Hancock
Proceedings of the 21st international conference on World Wide Web, 201-210, 2012
2532012
Negative Deceptive Opinion Spam
M Ott, C Cardie, JT Hancock
Proceedings of NAACL-HLT, 2013
2272013
Multi-aspect Sentiment Analysis with Topic Models
B Lu, M Ott, C Cardie, BK Tsou
Proceedings of the ICDM 2011 Workshop on Sentiment Elicitation from Natural …, 2011
1962011
Towards a general rule for identifying deceptive opinion spam
J Li, M Ott, C Cardie, E Hovy
Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014
1872014
Phrase-Based & Neural Unsupervised Machine Translation
G Lample, M Ott, A Conneau, L Denoyer, MA Ranzato
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
1812018
Understanding Back-Translation at Scale
S Edunov, M Ott, M Auli, D Grangier
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
1242018
fairseq: A fast, extensible toolkit for sequence modeling
M Ott, S Edunov, A Baevski, A Fan, S Gross, N Ng, D Grangier, M Auli
Proceedings of the 2019 Conference of the North American Chapter of the …, 2019
1062019
Scaling Neural Machine Translation
M Ott, S Edunov, D Grangier, M Auli
Proceedings of the Third Conference on Machine Translation (WMT), 2018
1032018
Classical Structured Prediction Losses for Sequence to Sequence Learning
S Edunov, M Ott, M Auli, D Grangier, MA Ranzato
Proceedings of NAACL-HLT 2018, 355-364, 2018
602018
Analyzing Uncertainty in Neural Machine Translation
M Ott, M Auli, D Grangier, MA Ranzato
Proceedings of the 35th International Conference on Machine Learning, 2018
422018
Identifying manipulated offerings on review portals
J Li, M Ott, C Cardie
Proceedings of the 2013 Conference on Empirical Methods in Natural Language …, 2013
392013
In Search of a Gold Standard in Studies of Deception
S Gokhman, J Hancock, P Prabhu, M Ott, C Cardie
Proceedings of the EACL 2012 Workshop on Computational Approaches to …, 2012
382012
Properties, prediction, and prevalence of useful user-generated comments for descriptive annotation of social media objects
E Momeni, C Cardie, M Ott
Seventh International AAAI Conference on Weblogs and Social Media, 2013
272013
Impact of mobility and timing on user-generated content
G Piccoli, M Ott
MIS Quarterly Executive 13 (3), 147-157, 2014
202014
The FLoRes Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English
F Guzmán, PJ Chen, M Ott, J Pino, G Lample, P Koehn, V Chaudhary, ...
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
172019
Mixture Models for Diverse Machine Translation: Tricks of the Trade
T Shen, M Ott, M Auli, MA Ranzato
Proceedings of the 36th International Conference on Machine Learning, 2019
132019
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
A Rives, S Goyal, J Meier, D Guo, M Ott, CL Zitnick, J Ma, R Fergus
bioRxiv, 622803, 2019
122019
Unsupervised cross-lingual representation learning at scale
A Conneau, K Khandelwal, N Goyal, V Chaudhary, G Wenzek, F Guzmán, ...
arXiv preprint arXiv:1911.02116, 2019
102019
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