Fetching the paper…
Reading the bibliography…
Rapid progress in Neural Machine Translation (NMT) systems over the last few years has been driven primarily towards improving translation quality, and as a secondary focus, improved robustness to input perturbations (e.g.
Linking artificial and human neural representations of language
Jon Gauthier and Roger Levy. 2019 · 1910
Earlier work this paper cites.
What does BERT learn from multiple-choice reading comprehension datasets?
Chenglei Si, Shuohang Wang, Min-Yen Kan, and Jing Jiang. 2019 · 1910
Earlier work this paper cites.
Sticking to the facts: Confident decoding for faithful data-to-text generation
Ran Tian, Shashi Narayan, Thibault Sellam, and Ankur P Parikh. 2020 · 1910
Earlier work this paper cites.
On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
Earlier work this paper cites.
Improving robustness of machine translation with synthetic noise
Vaibhav Vaibhav, Sumeet Singh, Craig Stewart, and Graham Neubig. 2019 · 1920
Earlier work this paper cites.
Syntactic structures
Noam Chomsky. 1957 · 1957
Earlier work this paper cites.
Binary codes capable of correcting deletions, insertions, and reversals
Vladimir I Levenshtein. 1966 · 1966
Earlier work this paper cites.
On the importance of word order information in cross-lingual sequence labeling
Zihan Liu, Genta Indra Winata, Samuel Cahyawijaya, Andrea Madotto, Zhaojiang Lin, and Pascale Fung. 2020 · 2001
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Catching the drift: Probabilistic content models, with applications to generation and summarization
Regina Barzilay and Lillian Lee. 2004 · 2004
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Clause restructuring for statistical machine translation
Michael Collins, Philipp Koehn, and Ivona Kučerová. 2005 · 2005
Earlier work this paper cites.
Meteor: An automatic metric for mt evaluation with high levels of correlation with human judgments
Alon Lavie and Abhaya Agarwal. 2007 · 2007
Earlier work this paper cites.
Modeling local coherence: An entity-based approach
Regina Barzilay and Mirella Lapata. 2008 · 2008
Earlier work this paper cites.
Coupling hierarchical word reordering and decoding in phrase-based statistical machine translation
Maxim Khalilov, José A. R. Fonollosa, and Mark Dras. 2009 · 2009
Earlier work this paper cites.
Context-free reordering, finite-state translation
Chris Dyer and Philip Resnik. 2010 · 2010
Earlier work this paper cites.
Beyond english-centric multilingual machine translation
Angela Fan, Shruti Bhosale, and Holger Schwenk et al. 2020 · 2010
Earlier work this paper cites.
Automatically learning source-side reordering rules for large scale machine translation
Dmitriy Genzel. 2010 · 2010
Earlier work this paper cites.
Source reordering using MaxEnt classifiers and supertags
Maxim Khalilov and Khalil Sima’an. 2010 · 2010
Earlier work this paper cites.
Thang M Pham, Trung Bui, Long Mai, and Anh Nguyen. 2020 · 2012
Earlier work this paper cites.
Pre-reordering for machine translation using transition-based walks on dependency parse trees
Antonio Valerio Miceli-Barone and Giuseppe Attardi. 2013 · 2013
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014 · 2014
Earlier work this paper cites.
An architecture for encoding sentence meaning in left mid-superior temporal cortex
Steven M Frankland and Joshua D Greene. 2015 · 2015
Cited alongside, same era.
Stanford neural machine translation systems for spoken language domain
Minh-Thang Luong and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
The boundaries of Babel: The brain and the enigma of impossible languages
Andrea Moro. 2015 · 2015
Cited alongside, same era.
Oriol Vinyals and Quoc Le. 2015 · 2015
Cited alongside, same era.
Impossible languages
Andrea Moro. 2016 · 2016
Cited alongside, same era.
Creating interactive macaronic interfaces for language learning
Adithya Renduchintala, Rebecca Knowles, Philipp Koehn, and Jason Eisner. 2016 · 2016
Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
Tom McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
Later among the works it cites.
A simple recipe towards reducing hallucination in neural surface realisation
Feng Nie, Jin-Ge Yao, Jinpeng Wang, Rong Pan, and Chin-Yew Lin. 2019 · 2019
Later among the works it cites.
Translating translationese: A two-step approach to unsupervised machine translation
Nima Pourdamghani, Nada Aldarrab, Marjan Ghazvininejad, Kevin Knight, and Jonathan May. 2019 · 2019
Later among the works it cites.
Do neural dialog systems use the conversation history effectively? an empirical study
Chinnadhurai Sankar, Sandeep Subramanian, Christopher Pal, Sarath Chandar, and Yoshua Bengio. 2019 · 2019
Later among the works it cites.
The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2019 · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Translating neuralese
Jacob Andreas, Anca Dragan, and Dan Klein. 2017 · 2017
Cited alongside, same era.
A challenge set approach to evaluating machine translation
Pierre Isabelle, Colin Cherry, and George Foster. 2017 · 2017
Cited alongside, same era.
Six challenges for neural machine translation
Philipp Koehn and Rebecca Knowles. 2017 · 2017
Cited alongside, same era.
Adversarial generation of natural language
Sai Rajeswar, Sandeep Subramanian, Francis Dutil, Christopher Pal, and Aaron Courville. 2017 · 2017
Cited alongside, same era.
Robsut wrod reocginiton via semi-character recurrent neural network
Keisuke Sakaguchi, Kevin Duh, Matt Post, and Benjamin Van Durme. 2017 · 2017
Cited alongside, same era.
The sentence superiority effect revisited
Joshua Snell and Jonathan Grainger. 2017 · 2017
Cited alongside, same era.
Advaug: Robust adversarial augmentation for neural machine translation
Yong Cheng, Lu Jiang, Wolfgang Macherey, and Jacob Eisenstein. 2020 · 2020
Later among the works it cites.
What bert is not: Lessons from a new suite of psycholinguistic diagnostics for language models
Allyson Ettinger. 2020 · 2020
Later among the works it cites.
The unreasonable volatility of neural machine translation models
Marzieh Fadaee and Christof Monz. 2020 · 2020
Later among the works it cites.
Type B reflexivization as an unambiguous testbed for multilingual multi-task gender bias
Ana Valeria González, Maria Barrett, Rasmus Hvingelby, Kellie Webster, and Anders Søgaard. 2020 · 2020
Later among the works it cites.
Are natural language inference models IMPPRESsive? Learning IMPlicature and PRESupposition
Paloma Jeretic, Alex Warstadt, Suvrat Bhooshan, and Adina Williams. 2020 · 2020
Later among the works it cites.
Cross-lingual alignment methods for multilingual BERT: A comparative study
Saurabh Kulshreshtha, Jose Luis Redondo Garcia, and Ching-Yun Chang. 2020 · 2020
Later among the works it cites.
Contextualized perturbation for textual adversarial attack
Dianqi Li, Yizhe Zhang, Hao Peng, Liqun Chen, Chris Brockett, Ming-Ting Sun, and Bill Dolan. 2020 · 2020
Later among the works it cites.
Does syntax need to grow on trees? sources of hierarchical inductive bias in sequence-to-sequence networks
R. Thomas McCoy, Robert Frank, and Tal Linzen. 2020 · 2020
Later among the works it cites.
Evaluating robustness to input perturbations for neural machine translation
Xing Niu, Prashant Mathur, Georgiana Dinu, and Yaser Al-Onaizan. 2020 · 2020
Later among the works it cites.
How to evaluate your dialogue system: Probe tasks as an alternative for token-level evaluation metrics
Prasanna Parthasarathi, Joelle Pineau, and Sarath Chandar. 2020 · 2020
Later among the works it cites.
Beyond accuracy: Behavioral testing of NLP models with CheckList
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2020
Later among the works it cites.
Unnatural language inference
Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, and Adina Williams. 2020 · 2020
Later among the works it cites.
OPUS-MT — Building open translation services for the World
Jörg Tiedemann and Santhosh Thottingal. 2020 · 2020
Later among the works it cites.
Similarity-aware neural machine translation: reducing human translator efforts by leveraging high-potential sentences with translation memory
Tianfu Zhang, Heyan Huang, Chong Feng, and Xiaochi Wei. 2020 · 2020
Later among the works it cites.
On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation
Wei Zhao, Goran Glavaš, Maxime Peyrard, Yang Gao, Robert West, and Steffen Eger. 2020 · 2020
Later among the works it cites.
Bert & family eat word salad: Experiments with text understanding
Ashim Gupta, Giorgi Kvernadze, and Vivek Srikumar. 2021 · 2021
Closest in time.
On hallucination and predictive uncertainty in conditional language generation
Yijun Xiao and William Yang Wang. 2021 · 2021
Closest in time.