526 citations · 1.4k across the 19 of their papers we have counts for
21 papers
MAD for Robust Reinforcement Learning in Machine Translation
Domenic Donato, Lei Yu, Wang Ling +1
We introduce a new distributed policy gradient algorithm and show that it outperforms existing reward-aware training procedures such as REINFORCE, minimum risk training (MRT) and p…
Enabling arbitrary translation objectives with Adaptive Tree Search
Wang Ling, Wojciech Stokowiec, Domenic Donato +4
We introduce an adaptive tree search algorithm, that can find high-scoring outputs under translation models that make no assumptions about the form or structure of the search objec…
A Mutual Information Maximization Perspective of Language Representation Learning
Lingpeng Kong, Cyprien de Masson d'Autume, Wang Ling +3
We show state-of-the-art word representation learning methods maximize an objective function that is a lower bound on the mutual information between different parts of a word seque…
Better Document-Level Machine Translation with Bayes' Rule
Lei Yu, Laurent Sartran, Wojciech Stokowiec +4
We show that Bayes' rule provides an effective mechanism for creating document translation models that can be learned from only parallel sentences and monolingual documents---a com…
Learning and Evaluating General Linguistic Intelligence
Dani Yogatama, Cyprien de Masson d'Autume, Jerome Connor +8
We define general linguistic intelligence as the ability to reuse previously acquired knowledge about a language's lexicon, syntax, semantics, and pragmatic conventions to adapt to…
Variational Smoothing in Recurrent Neural Network Language Models
Lingpeng Kong, Gabor Melis, Wang Ling +2
We present a new theoretical perspective of data noising in recurrent neural network language models (Xie et al., 2017). We show that each variant of data noising is an instance of…