Synthetic and Natural Noise Both Break Neural Machine Translation

6 November 2017

Papers citing "Synthetic and Natural Noise Both Break Neural Machine Translation"

10 / 160 papers shown

Title
Adversarial Over-Sensitivity and Over-Stability Strategies for Dialogue Models Tong Niu Joey Tianyi Zhou AAML 21 85 0 06 Sep 2018
Stress Test Evaluation for Natural Language Inference Aakanksha Naik Abhilasha Ravichander Norman M. Sadeh Carolyn Rose Graham Neubig ELM 36 370 0 02 Jun 2018
On the Impact of Various Types of Noise on Neural Machine Translation Huda Khayrallah Philipp Koehn AAML 34 217 0 31 May 2018
Towards Robust Neural Machine Translation Yong Cheng Zhaopeng Tu Fandong Meng Junjie Zhai Yang Liu AAML 19 161 0 16 May 2018
Interpretable Adversarial Perturbation in Input Embedding Space for Text Motoki Sato Jun Suzuki Hiroyuki Shindo Yuji Matsumoto 16 188 0 08 May 2018
The Fine Line between Linguistic Generalization and Failure in Seq2Seq-Attention Models Noah Weber L. Shekhar Niranjan Balasubramanian 98 30 0 03 May 2018
Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates Taku Kudo 22 1,147 0 29 Apr 2018
Investigating Backtranslation in Neural Machine Translation Alberto Poncelas D. Shterionov Andy Way Gideon Maillette de Buy Wenniger Peyman Passban 30 143 0 17 Apr 2018
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 38 596 0 31 Oct 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016