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Machine translation quality estimation (QE) predicts human judgements of a translation hypothesis without seeing the reference.
Pay less attention with lightweight and dynamic convolutions
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Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
George Doddington. 2002 · 2002
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BLEU: A method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Confidence estimation for machine translation
John Blatz, Erin Fitzgerald, George Foster, Simona Gandrabur, Cyril Goutte, Alex Kulesza, Alberto Sanchis, and Nicola Ueffing. 2004 · 2004
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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A study of translation edit rate with targeted human annotation
Matthew Snover, Bonnie Dorr, Richard Schwartz, Linnea Micciulla, and John Makhoul. 2006 · 2006
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GRADE: Automatic graph-enhanced coherence metric for evaluating open-domain dialogue systems
Lishan Huang, Zheng Ye, Jinghui Qin, Liang Lin, and Xiaodan Liang. 2020 · 2010
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Evaluating the output of machine translation systems
Alon Lavie. 2010 · 2010
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Machine translation evaluation versus quality estimation
Lucia Specia, Dhwaj Raj, and Marco Turchi. 2010 · 2010
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Minimum bayes risk decoding and system combination based on a recursion for edit distance
Haihua Xu, Daniel Povey, Lidia Mangu, and Jie Zhu. 2011 · 2011
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Multi-target regression with rule ensembles
Timo Aho, Bernard Ženko, Sašo Džzeroski, Tapio Elomaa, and Carla Brodley. 2012 · 2012
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Quality estimation for machine translation output using linguistic analysis and decoding features
Eleftherios Avramidis. 2012 · 2012
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Linguistic features for quality estimation
Mariano Felice and Lucia Specia. 2012 · 2012
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Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
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QuEst: A translation quality estimation framework
Lucia Specia, Kashif Shah, José GC De Souza, and Trevor Cohn. 2013 · 2013
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Findings of the 2014 workshop on statistical machine translation
Ondrej Bojar, Christian Buck, Christian Federmann, Barry Haddow, Philipp Koehn, Johannes Leveling, Christof Monz, Pavel Pecina, Matt Post, Herve Saint-Amand, Radu Soricut, Lucia Specia, and Aleš Tamchyna. 2014 · 2014
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Machine translation quality estimation across domains
José GC de Souza, Marco Turchi, and Matteo Negri. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Quality estimation from scratch (quetch): Deep learning for word-level translation quality estimation
Julia Kreutzer, Shigehiko Schamoni, and Stefan Riezler. 2015 · 2015
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chrF: character n-gram f-score for automatic MT evaluation
Maja Popović. 2015 · 2015
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Recurrent neural network based translation quality estimation
Hyun Kim and Jong-Hyeok Lee. 2016 · 2016
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Unbabel’s participation in the wmt16 word-level translation quality estimation shared task
André FT Martins, Ramón Fernandez Astudillo, Chris Hokamp, and Fabio Kepler. 2016 · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Shef-lium-nn: Sentence level quality estimation with neural network features
Kashif Shah, Fethi Bougares, Loïc Barrault, and Lucia Specia. 2016 · 2016
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Improving machine translation quality estimation with neural network features
Zhiming Chen, Yiming Tan, Chenlin Zhang, Qingyu Xiang, Lilin Zhang, Maoxi Li, and Mingwen Wang. 2017 · 2017
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Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N Dauphin. 2017 · 2017
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Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, and Noah A Smith. 2018 · 2018
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DeepQuest: A framework for neural-based quality estimation
Julia Ive, Frédéric Blain, and Lucia Specia. 2018 · 2018
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A unified neural network for quality estimation of machine translation
Maoxi Li, Qingyu Xiang, Zhiming Chen, and Mingwen Wang. 2018 · 2018
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Scaling neural machine translation
Myle Ott, Sergey Edunov, David Grangier, and Michael Auli. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020a · 2020
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Intermediate self-supervised learning for machine translation quality estimation
Raphael Rubino and Eiichiro Sumita. 2020 · 2020
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BLEURT: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
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Findings of the WMT 2020 shared task on quality estimation
Lucia Specia, Frédéric Blain, Marina Fomicheva, Erick Fonseca, Vishrav Chaudhary, Francisco Guzmán, and André F. T. Martins. 2020 · 2020
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Are we estimating or guesstimating translation quality?
Shuo Sun, Francisco Guzmán, and Lucia Specia. 2020 · 2020
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Self-paced learning for neural machine translation
Yu Wan, Baosong Yang, Derek F Wong, Yikai Zhou, Lidia S Chao, Haibo Zhang, and Boxing Chen. 2020 · 2020
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Quality estimation for machine translation
Lucia Specia, Carolina Scarton, and Gustavo Henrique Paetzold. 2018 · 2018
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Ruber: An unsupervised method for automatic evaluation of open-domain dialog systems
Chongyang Tao, Lili Mou, Dongyan Zhao, and Rui Yan. 2018 · 2018
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Quality estimation with force-decoded attention and cross-lingual embeddings
Elizaveta Yankovskaya, Andre Tättar, and Mark Fishel. 2018 · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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OpenKiwi: An open source framework for quality estimation
Fábio Kepler, Jonay Trénous, Marcos Treviso, Miguel Vera, and André FT Martins. 2019 · 2019
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Results of the WMT19 metrics shared task: Segment-level and strong MT systems pose big challenges
Qingsong Ma, Johnny Wei, Ondřej Bojar, and Yvette Graham. 2019 · 2019
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On the inference calibration of neural machine translation
Shuo Wang, Zhaopeng Tu, Shuming Shi, and Yang Liu. 2020 · 2020
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Directqe: Direct pretraining for machine translation quality estimation
Qu Cui, Shujian Huang, Jiahuan Li, Xiang Geng, Zaixiang Zheng, Guoping Huang, and Jiajun Chen. 2021 · 2021
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Comparative analysis of current approaches to quality estimation for neural machine translation
Sugyeong Eo, Chanjun Park, Hyeonseok Moon, Jaehyung Seo, and Heuiseok Lim. 2021 · 2021
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Beyond english-centric multilingual machine translation
Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, et al. 2021 · 2021
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Uncertainty-aware machine translation evaluation
Taisiya Glushkova, Chrysoula Zerva, Ricardo Rei, and André FT Martins. 2021 · 2021
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Quality estimation using dual encoders with transfer learning
Dam Heo, WonKee Lee, Baikjin Jung, and Jong-Hyeok Lee. 2021 · 2021
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q 2 q^{2} : Evaluating factual consistency in knowledge-grounded dialogues via question generation and question answering
Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, and Omri Abend. 2021 · 2021
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To ship or not to ship: An extensive evaluation of automatic metrics for machine translation
Tom Kocmi, Christian Federmann, Roman Grundkiewicz, Marcin Junczys-Dowmunt, Hitokazu Matsushita, and Arul Menezes. 2021 · 2021
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CCMatrix: Mining billions of high-quality parallel sentences on the web
Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Édouard Grave, Armand Joulin, and Angela Fan. 2021 · 2021
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Findings of the WMT 2021 shared task on quality estimation
Lucia Specia, Frédéric Blain, Marina Fomicheva, Chrysoula Zerva, Zhenhao Li, Vishrav Chaudhary, and André FT Martins. 2021 · 2021
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Deploying MT quality estimation on a large scale: Lessons learned and open questions
Aleš Tamchyna. 2021 · 2021
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Direct exploitation of attention weights for translation quality estimation
Lisa Yankovskaya and Mark Fishel. 2021 · 2021
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Backtranslation feedback improves user confidence in MT, not quality
Vilém Zouhar, Michal Novák, Matúš Žilinec, Ondřej Bojar, Mateo Obregón, Robin L Hill, Frédéric Blain, Marina Fomicheva, Lucia Specia, and Lisa Yankovskaya. 2021 · 2021
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Bias mitigation in machine translation quality estimation
Hanna Behnke, Marina Fomicheva, and Lucia Specia. 2022 · 2022
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Prequel: Quality estimation of machine translation outputs in advance
Shachar Don-Yehiya, Leshem Choshen, and Omri Abend. 2022 · 2022
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Quality-aware decoding for neural machine translation
Patrick Fernandes, António Farinhas, Ricardo Rei, José GC de Souza, Perez Ogayo, Graham Neubig, and André FT Martins. 2022 · 2022
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A quality estimation and quality evaluation tool for the translation industry
Elena Murgolo, Javad Pourmostafa Roshan Sharami, and Dimitar Shterionov. 2022 · 2022
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UniTE: Unified translation evaluation
Yu Wan, Dayiheng Liu, Baosong Yang, Haibo Zhang, Boxing Chen, Derek Wong, and Lidia Chao. 2022 · 2022
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Fusing sentence embeddings into LSTM-based autoregressive language models
Vilém Zouhar, Marius Mosbach, and Dietrich Klakow. 2022 · 2022
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