655 citations · 1.3k across the 31 of their papers we have counts for
6 papers · 1 filter
Understanding Knowledge Distillation in Non-autoregressive Machine Translation
Chunting Zhou, Graham Neubig, Jiatao Gu
Non-autoregressive machine translation (NAT) systems predict a sequence of output tokens in parallel, achieving substantial improvements in generation speed compared to autoregress…
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
Xuezhe Ma, Chunting Zhou, Xian Li +2
Most sequence-to-sequence (seq2seq) models are autoregressive; they generate each token by conditioning on previously generated tokens. In contrast, non-autoregressive seq2seq mode…
Handling Syntactic Divergence in Low-resource Machine Translation
Chunting Zhou, Xuezhe Ma, Junjie Hu +1
Despite impressive empirical successes of neural machine translation (NMT) on standard benchmarks, limited parallel data impedes the application of NMT models to many language pair…
Density Matching for Bilingual Word Embedding
Chunting Zhou, Xuezhe Ma, Di Wang +1
Recent approaches to cross-lingual word embedding have generally been based on linear transformations between the sets of embedding vectors in the two languages. In this paper, we…
The ARIEL-CMU Systems for LoReHLT18
Aditi Chaudhary, Siddharth Dalmia, Junjie Hu +27
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery a…
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders
Xuezhe Ma, Chunting Zhou, Eduard Hovy
Variational Autoencoder (VAE), a simple and effective deep generative model, has led to a number of impressive empirical successes and spawned many advanced variants and theoretica…