318 citations · 603 across the 5 of their papers we have counts for
5 papers
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Myle Ott, Sergey Edunov, Alexei Baevski +5
fairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text…
Pre-trained Language Model Representations for Language Generation
Sergey Edunov, Alexei Baevski, Michael Auli
Pre-trained language model representations have been successful in a wide range of language understanding tasks. In this paper, we examine different strategies to integrate pre-tra…
Pay Less Attention with Lightweight and Dynamic Convolutions
Felix Wu, Angela Fan, Alexei Baevski +2
Self-attention is a useful mechanism to build generative models for language and images. It determines the importance of context elements by comparing each element to the current t…
Mixture Models for Diverse Machine Translation: Tricks of the Trade
Tianxiao Shen, Myle Ott, Michael Auli +1
Mixture models trained via EM are among the simplest, most widely used and well understood latent variable models in the machine learning literature. Surprisingly, these models hav…
Vocabulary Selection Strategies for Neural Machine Translation
Gurvan L'Hostis, David Grangier, Michael Auli
Classical translation models constrain the space of possible outputs by selecting a subset of translation rules based on the input sentence. Recent work on improving the efficiency…