1.6k citations · 3.3k across the 22 of their papers we have counts for
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A Hybrid Morpheme-Word Representation for Machine Translation of Morphologically Rich Languages
Minh-Thang Luong, Preslav Nakov, Min-Yen Kan
We propose a language-independent approach for improving statistical machine translation for morphologically rich languages using a hybrid morpheme-word representation where the ba…
Self-training with Noisy Student improves ImageNet classification
Qizhe Xie, Minh-Thang Luong, Eduard Hovy +1
We present Noisy Student Training, a semi-supervised learning approach that works well even when labeled data is abundant. Noisy Student Training achieves 88.4% top-1 accuracy on I…
Findings of the Third Workshop on Neural Generation and Translation
Hiroaki Hayashi, Yusuke Oda, Alexandra Birch +5
This document describes the findings of the Third Workshop on Neural Generation and Translation, held in concert with the annual conference of the Empirical Methods in Natural Lang…
Selfie: Self-supervised Pretraining for Image Embedding
Trieu H. Trinh, Minh-Thang Luong, Quoc V. Le
We introduce a pretraining technique called Selfie, which stands for SELFie supervised Image Embedding. Selfie generalizes the concept of masked language modeling of BERT (Devlin e…
BAM! Born-Again Multi-Task Networks for Natural Language Understanding
Kevin Clark, Minh-Thang Luong, Urvashi Khandelwal +2
It can be challenging to train multi-task neural networks that outperform or even match their single-task counterparts. To help address this, we propose using knowledge distillatio…
Unsupervised Data Augmentation for Consistency Training
Qizhe Xie, Zihang Dai, Eduard Hovy +2
Semi-supervised learning lately has shown much promise in improving deep learning models when labeled data is scarce. Common among recent approaches is the use of consistency train…