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Sequence-Level Knowledge Distillation
Yoon Kim
|
Alexander M. Rush
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Paper Details:
Month: November
Year: 2016
Location: Austin, Texas
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Dynamic Data Selection for Neural Machine Translation
Marlies van der Wees
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Arianna Bisazza
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Christof Monz
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Towards Compact and Fast Neural Machine Translation Using a Combined Method
Xiaowei Zhang
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Wei Chen
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Feng Wang
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Shuang Xu
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Bo Xu
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Unfolding and Shrinking Neural Machine Translation Ensembles
Felix Stahlberg
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Bill Byrne
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Natural Language Processing with Small Feed-Forward Networks
Jan A. Botha
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Emily Pitler
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Ji Ma
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Anton Bakalov
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Alex Salcianu
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David Weiss
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Ryan McDonald
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Slav Petrov
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A Stable and Effective Learning Strategy for Trainable Greedy Decoding
Yun Chen
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Victor O.K. Li
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Kyunghyun Cho
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Samuel Bowman
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Compact Personalized Models for Neural Machine Translation
Joern Wuebker
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Patrick Simianer
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John DeNero
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Semi-Supervised Sequence Modeling with Cross-View Training
Kevin Clark
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Minh-Thang Luong
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Christopher D. Manning
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Quoc Le
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Frustratingly Easy Model Ensemble for Abstractive Summarization
Hayato Kobayashi
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Greedy Search with Probabilistic N-gram Matching for Neural Machine Translation
Chenze Shao
|
Xilin Chen
|
Yang Feng
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Efficient Sequence Learning with Group Recurrent Networks
Fei Gao
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Lijun Wu
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Li Zhao
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Tao Qin
|
Xueqi Cheng
|
Tie-Yan Liu
|
Parsing Tweets into Universal Dependencies
Yijia Liu
|
Yi Zhu
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Wanxiang Che
|
Bing Qin
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Nathan Schneider
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Noah A. Smith
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Recurrent Neural Networks as Weighted Language Recognizers
Yining Chen
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Sorcha Gilroy
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Andreas Maletti
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Jonathan May
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Kevin Knight
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Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations
Sosuke Kobayashi
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A Teacher-Student Framework for Zero-Resource Neural Machine Translation
Yun Chen
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Yang Liu
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Yong Cheng
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Victor O.K. Li
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Speeding Up Neural Machine Translation Decoding by Shrinking Run-time Vocabulary
Xing Shi
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Kevin Knight
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Distilling Knowledge for Search-based Structured Prediction
Yijia Liu
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Wanxiang Che
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Huaipeng Zhao
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Bing Qin
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Ting Liu
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YNU_Deep at SemEval-2018 Task 11: An Ensemble of Attention-based BiLSTM Models for Machine Comprehension
Peng Ding
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Xiaobing Zhou
|
Stronger Baselines for Trustable Results in Neural Machine Translation
Michael Denkowski
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Graham Neubig
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Findings of the Second Workshop on Neural Machine Translation and Generation
Alexandra Birch
|
Andrew Finch
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Minh-Thang Luong
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Graham Neubig
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Yusuke Oda
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Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation
Huda Khayrallah
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Brian Thompson
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Kevin Duh
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Philipp Koehn
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Marian: Cost-effective High-Quality Neural Machine Translation in C++
Marcin Junczys-Dowmunt
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Kenneth Heafield
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Hieu Hoang
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Roman Grundkiewicz
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Anthony Aue
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https://github.com/harvardnlp/nmt-android
https://github.com/harvardnlp/seq2seq-attn
http://statmt.org/wmt14
https://sites.google.com/site/iwsltevaluation2015/mt-track
Field Of Study
Linguistic Trends
Embeddings
Task
Summarization
Machine Translation
Approach
Deep Learning
Structured Prediction
Unsupervised Learning
Language
English
French
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