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Neural sequence generation models are known to "hallucinate", by producing outputs that are unrelated to the source text.
On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020a · 1919
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On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020b · 1919
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Measuring nominal scale agreement among many raters
Joseph L Fleiss. 1971 · 1971
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The JRC-Acquis: A multilingual aligned parallel corpus with 20+ languages
Ralf Steinberger, Bruno Pouliquen, Anna Widiger, Camelia Ignat, Tomaž Erjavec, Dan Tufiş, and Dániel Varga. 2006 · 2006
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Moses: Open source toolkit for statistical machine translation
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondřej Bojar, Alexandra Constantin, and Evan Herbst. 2007 · 2007
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Estimating the sentence-level quality of machine translation systems
Lucia Specia, Marco Turchi, Nicola Cancedda, Nello Cristianini, and Marc Dymetman. 2009 · 2009
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Applied logistic regression , volume 398
David W Hosmer Jr, Stanley Lemeshow, and Rodney X Sturdivant. 2013 · 2013
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Deep inside convolutional networks: visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman. 2014 · 2014
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On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
Sebastian Bach, Alexander Binder, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller, and Wojciech Samek. 2015 · 2015
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The IWSLT 2015 evaluation campaign
Mauro Cettolo, Jan Niehues, Sebastian Stüker, Luisa Bentivogli, Roldano Cattoni, and Marcello Federico. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Layer-wise relevance propagation for neural networks with local renormalization layers
Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, Klaus-Robert Müller, and Wojciech Samek. 2016 · 2016
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Visualizing and understanding neural models in NLP
Jiwei Li, Xinlei Chen, Eduard Hovy, and Dan Jurafsky. 2016a · 2016
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A causal framework for explaining the predictions of black-box sequence-to-sequence models
David Alvarez-Melis and Tommi Jaakkola. 2017 · 2017
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Visualizing and understanding neural machine translation
Yanzhuo Ding, Yang Liu, Huanbo Luan, and Maosong Sun. 2017 · 2017
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Predictor-estimator using multilevel task learning with stack propagation for neural quality estimation
Hyun Kim, Jong-Hyeok Lee, and Seung-Hoon Na. 2017 · 2017
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Confidence Through Attention
Matīss Rikters and Mark Fishel. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Challenges in data-to-document generation
Sam Wiseman, Stuart Shieber, and Alexander Rush. 2017 · 2017
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Findings of the 2018 conference on machine translation (WMT18)
Ondrej Bojar, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Philipp Koehn, and Christof Monz. 2018 · 2018
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Findings of the E2E NLG challenge
Ondřej Dušek, Jekaterina Novikova, and Verena Rieser. 2018 · 2018
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On adversarial examples for character-level neural machine translation
Javid Ebrahimi, Daniel Lowd, and Dejing Dou. 2018 · 2018
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Pathologies of neural models make interpretations difficult
Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, and Jordan Boyd-Graber. 2018 · 2018
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Sharp nearby, fuzzy far away: How neural language models use context
Urvashi Khandelwal, He He, Peng Qi, and Dan Jurafsky. 2018 · 2018
Cited alongside, same era.
Hallucinations in neural machine translation
Katherine Lee, Orhan Firat, Ashish Agarwal, Clara Fannjiang, and David Sussillo. 2018 · 2018
Cited alongside, same era.
An analysis of source context dependency in neural machine translation
Xutai Ma, Ke Li, and Philipp Koehn. 2018 · 2018
Cited alongside, same era.
Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT
Marianna Martindale and Marine Carpuat. 2018 · 2018
Cited alongside, same era.
The University of Maryland’s Chinese-English neural machine translation systems at WMT18
Weijia Xu and Marine Carpuat. 2018 · 2018
Cited alongside, same era.
Quality estimation with force-decoded attention and cross-lingual embeddings
COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020a · 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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On exposure bias, hallucination and domain shift in neural machine translation
Chaojun Wang and Rico Sennrich. 2020 · 2020
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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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Findings of the 2021 conference on machine translation (WMT21)
Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ondřej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-jussa, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, and Marcos Zampieri. 2021 · 2021
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Elizaveta Yankovskaya, Andre Tättar, and Mark Fishel. 2018 · 2018
Cited alongside, same era.
Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
Mikel Artetxe and Holger Schwenk. 2019 · 2019
Cited alongside, same era.
Saliency-driven Word Alignment Interpretation for Neural Machine Translation
Shuoyang Ding, Hainan Xu, and Philipp Koehn. 2019 · 2019
Cited alongside, same era.
Ranking generated summaries by correctness: An interesting but challenging application for natural language inference
Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, Ido Dagan, and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
The FLORES evaluation datasets for low-resource machine translation: Nepali–English and Sinhala–English
Francisco Guzmán, Peng-Jen Chen, Myle Ott, Juan Pino, Guillaume Lample, Philipp Koehn, Vishrav Chaudhary, and Marc’Aurelio Ranzato. 2019 · 2019
Cited alongside, same era.
Towards understanding neural machine translation with word importance
Shilin He, Zhaopeng Tu, Xing Wang, Longyue Wang, Michael Lyu, and Shuming Shi. 2019 · 2019
Cited alongside, same era.
Training on synthetic noise improves robustness to natural noise in machine translation
Vladimir Karpukhin, Omer Levy, Jacob Eisenstein, and Marjan Ghazvininejad. 2019 · 2019
Cited alongside, same era.
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On the dangers of stochastic parrots: Can language models be too big?
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021 · 2021
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Beyond noise: Mitigating the impact of fine-grained semantic divergences on neural machine translation
Eleftheria Briakou and Marine Carpuat. 2021 · 2021
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The University of Edinburgh’s English-German and English-Hausa submissions to the WMT21 news translation task
Pinzhen Chen, Jindřich Helcl, Ulrich Germann, Laurie Burchell, Nikolay Bogoychev, Antonio Valerio Miceli Barone, Jonas Waldendorf, Alexandra Birch, and Kenneth Heafield. 2021 · 2021
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The Curious Case of Hallucinations in Neural Machine Translation
Vikas Raunak, Arul Menezes, and Marcin Junczys-Dowmunt. 2021 · 2021
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Sashank Santhanam, Behnam Hedayatnia, Spandana Gella, Aishwarya Padmakumar, Seokhwan Kim, Yang Liu, and Dilek Hakkani-Tur. 2021 · 2021
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WikiMatrix: Mining 135M parallel sentences in 1620 language pairs from Wikipedia
Holger Schwenk, Vishrav Chaudhary, Shuo Sun, Hongyu Gong, and Francisco Guzmán. 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 F. T. Martins. 2021 · 2021
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Is this translation error critical?: Classification-based human and automatic machine translation evaluation focusing on critical errors
Katsuhito Sudoh, Kosuke Takahashi, and Satoshi Nakamura. 2021 · 2021
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Multilingual machine translation evaluation metrics fine-tuned on pseudo-negative examples for WMT 2021 metrics task
Kosuke Takahashi, Yoichi Ishibashi, Katsuhito Sudoh, and Satoshi Nakamura. 2021 · 2021
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Analyzing the source and target contributions to predictions in neural machine translation
Elena Voita, Rico Sennrich, and Ivan Titov. 2021 · 2021
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On hallucination and predictive uncertainty in conditional language generation
Yijun Xiao and William Yang Wang. 2021 · 2021
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Detecting hallucinated content in conditional neural sequence generation
Chunting Zhou, Graham Neubig, Jiatao Gu, Mona Diab, Francisco Guzmán, Luke Zettlemoyer, and Marjan Ghazvininejad. 2021 · 2021
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Looking for a needle in a haystack: A comprehensive study of hallucinations in neural machine translation
Nuno M. Guerreiro, Elena Voita, and André F. T. Martins. 2022 · 2022
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Bitext mining using distilled sentence representations for low-resource languages
Kevin Heffernan, Onur Çelebi, and Holger Schwenk. 2022 · 2022
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Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Yejin Bang, Andrea Madotto, and Pascale Fung. 2022 · 2022
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Rare but severe neural machine translation errors induced by minimal deletion: An empirical study on Chinese and English
Ruikang Shi, Alvin Grissom II, and Duc Minh Trinh. 2022 · 2022
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Findings of the wmt 2022 shared task on quality estimation
Chrysoula Zerva, Frédéric Blain, Ricardo Rei, Piyawat Lertvittayakumjorn, José G. C. de Souza, Steffen Eger, Diptesh Kanojia, Duarte Alves, Constantin Orăsan, Marina Fomicheva, André F. T. Martins, and Lucia Specia. 2022 · 2022
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