Myle Ott

Research Engineer

Facebook AI Research
I am a Research Engineer in Facebook’s AI Research group (FAIR), focusing on projects in dialogue, machine translation and text generation. Prior to Facebook, I completed my PhD at Cornell University in their NLP group, where my research explored approaches for identifying deception and sentiment in social media text.

Interests

Machine learning, natural language processing, and machine translation.

Personal Website
Personal Website

Latest Publications

The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English

Francisco (Paco) Guzman, Peng-Jen Chen, Myle Ott, Juan Pino, Guillaume Lample, Philipp Koehn, Vishrav Chaudhary, Marc'Aurelio Ranzato

EMNLP - October 31, 2019

Mixture Models for Diverse Machine Translation: Tricks of the Trade

Tianxiao Shen, Myle Ott, Michael Auli, Marc'Aurelio Ranzato

ICML - June 10, 2019

FAIRSEQ: A Fast, Extensible Toolkit for Sequence Modeling

Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli

NAACL - June 3, 2019

Understanding Back-Translation at Scale

Sergey Edunov, Myle Ott, Michael Auli, David Grangier

EMNLP 2018 - October 31, 2018

Phrase-Based & Neural Unsupervised Machine Translation

Guillaume Lample, Myle Ott, Alexis Conneau, Ludovic Denoyer, Marc'Aurelio Ranzato

EMNLP 2018 - October 31, 2018

Scaling Neural Machine Translation

Myle Ott, Sergey Edunov, David Grangier, Michael Auli

WMT 2018 - October 30, 2018

Analyzing Uncertainty in Neural Machine Translation

Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato

ICML 2018 - July 13, 2018

Classical Structured Prediction Losses for Sequence to Sequence Learning

Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato

NAACL 2018 - June 1, 2018