Fetching the paper…
Reading the bibliography…
Machine Translation (MT) is undergoing a paradigm shift, with systems based on fine-tuned large language models (LLM) becoming increasingly competitive with traditional encoder-decoder models trained specifically for translation tasks.
Minimum Bayes-risk decoding for statistical machine translation
Shankar Kumar and William Byrne. 2004 · 2004
Earlier work this paper cites.
chrf: character n-gram f-score for automatic MT evaluation
Maja Popovic. 2015 · 2015
Earlier work this paper cites.
Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
Earlier work this paper cites.
Fasttext.zip: Compressing text classification models
Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Hérve Jégou, and Tomas Mikolov. 2016 · 2016
Earlier work this paper cites.
Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
Earlier work this paper cites.
Naver labs Europe’s systems for the WMT19 machine translation robustness task
Alexandre Berard, Ioan Calapodescu, and Claude Roux. 2019 · 2019
Earlier work this paper cites.
Hallucinations in neural machine translation
Katherine Lee, Orhan Firat, Ashish Agarwal, Clara Fannjiang, and David Sussillo. 2019 · 2019
Earlier work this paper cites.
Is MAP decoding all you need? the inadequacy of the mode in neural machine translation
Bryan Eikema and Wilker Aziz. 2020 · 2020
Earlier work this paper cites.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
Earlier work this paper cites.
COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020 · 2020
Earlier work this paper cites.
The curious case of hallucinations in neural machine translation
Vikas Raunak, Arul Menezes, and Marcin Junczys-Dowmunt. 2021 · 2021
Earlier work this paper cites.
Analyzing the source and target contributions to predictions in neural machine translation
Elena Voita, Rico Sennrich, and Ivan Titov. 2021 · 2021
Earlier work this paper cites.
Language-agnostic BERT sentence embedding
Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, Naveen Arivazhagan, and Wei Wang. 2022 · 2022
Earlier work this paper cites.
Towards opening the black box of neural machine translation: Source and target interpretations of the transformer
Javier Ferrando, Gerard I. Gállego, Belen Alastruey, Carlos Escolano, and Marta R. Costa-jussà. 2022a · 2022
Earlier work this paper cites.
Measuring the mixing of contextual information in the transformer
Javier Ferrando, Gerard I. Gállego, and Marta R. Costa-jussà. 2022b · 2022
Cited alongside, same era.
High quality rather than high model probability: Minimum bayes risk decoding with neural metrics
Markus Freitag, David Grangier, Qijun Tan, and Bowen Liang. 2022 · 2022
Cited alongside, same era.
Truncation sampling as language model desmoothing
John Hewitt, Christopher Manning, and Percy Liang. 2022 · 2022
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
Cited alongside, same era.
Findings of the 2022 conference on machine translation (WMT22)
Tom Kocmi, Rachel Bawden, Ondřej Bojar, Anton Dvorkovich, Christian Federmann, Mark Fishel, Thamme Gowda, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Rebecca Knowles, Philipp Koehn, Christof Monz, Makoto Morishita, Masaaki Nagata, Toshiaki Nakazawa, Michal Novák, Martin Popel, and Maja Popović. 2022 · 2022
Cited alongside, same era.
Contrastive decoding: Open-ended text generation as optimization
Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, and Mike Lewis. 2023 · 2023
Later among the works it cites.
Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, and Chelsea Finn. 2023 · 2023
Later among the works it cites.
Contrastive search is what you need for neural text generation
Yixuan Su and Nigel Collier. 2023 · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin R. Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Daniel M. Bikel, Lukas Blecher, Cristian Cantón Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony S. Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel M. Kloumann, A. V. Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, R. Subramanian, Xia Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zhengxu Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Marta R. Costa-jussà NLLB Team, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, Janice Lam, Daniel Licht, Jean Maillard, Anna Sun, Skyler Wang, Guillaume Wenzek, Al Youngblood, Bapi Akula, Loic Barrault, Gabriel Mejia Gonzalez, Prangthip Hansanti, John Hoffman, Semarley Jarrett, Kaushik Ram Sadagopan, Dirk Rowe, Shannon Spruit, Chau Tran, Pierre Andrews, Necip Fazil Ayan, Shruti Bhosale, Sergey Edunov, Angela Fan, Cynthia Gao, Vedanuj Goswami, Francisco Guzmán, Philipp Koehn, Alexandre Mourachko, Christophe Ropers, Safiyyah Saleem, Holger Schwenk, and Jeff Wang. 2022 · 2022
Cited alongside, same era.
SALTED: A framework for SAlient long-tail translation error detection
Vikas Raunak, Matt Post, and Arul Menezes. 2022 · 2022
Cited alongside, same era.
Searching for COMETINHO: The little metric that could
Ricardo Rei, Ana C Farinha, José G.C. de Souza, Pedro G. Ramos, André F.T. Martins, Luisa Coheur, and Alon Lavie. 2022 · 2022
Cited alongside, same era.
BLASER: A text-free speech-to-speech translation evaluation metric
Mingda Chen, Paul-Ambroise Duquenne, Pierre Andrews, Justine Kao, Alexandre Mourachko, Holger Schwenk, and Marta R. Costa-jussà. 2023 · 2023
Cited alongside, same era.
HalOmi: A manually annotated benchmark for multilingual hallucination and omission detection in machine translation
David Dale, Elena Voita, Janice Lam, Prangthip Hansanti, Christophe Ropers, Elahe Kalbassi, Cynthia Gao, Loic Barrault, and Marta Costa-jussà. 2023b · 2023
Cited alongside, same era.
Epsilon sampling rocks: Investigating sampling strategies for minimum Bayes risk decoding for machine translation
Markus Freitag, Behrooz Ghorbani, and Patrick Fernandes. 2023 · 2023
Cited alongside, same era.
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2023 · 2023
Cited alongside, same era.
Later among the works it cites.
Understanding and detecting hallucinations in neural machine translation via model introspection
Weijia Xu, Sweta Agrawal, Eleftheria Briakou, Marianna J Martindale, and Marine Carpuat. 2023 · 2023
Later among the works it cites.
Tower: An open multilingual large language model for translation-related tasks
Duarte Miguel Alves, José Pombal, Nuno M Guerreiro, Pedro Henrique Martins, João Alves, Amin Farajian, Ben Peters, Ricardo Rei, Patrick Fernandes, Sweta Agrawal, Pierre Colombo, José G. C. de Souza, and Andre Martins. 2024 · 2024
Later among the works it cites.
Aya 23: Open weight releases to further multilingual progress
Viraat Aryabumi, John Dang, Dwarak Talupuru, Saurabh Dash, David Cairuz, Hangyu Lin, Bharat Venkitesh, Madeline Smith, Jon Ander Campos, Yi Chern Tan, Kelly Marchisio, Max Bartolo, Sebastian Ruder, Acyr Locatelli, Julia Kreutzer, Nick Frosst, Aidan Gomez, Phil Blunsom, Marzieh Fadaee, Ahmet Üstün, and Sara Hooker. 2024 · 2024
Later among the works it cites.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
Later among the works it cites.
Ikun for wmt24 general mt task: Llms are here for multilingual machine translation
Baohao Liao, Christian Herold, Shahram Khadivi, and Christof Monz. 2024 · 2024
Later among the works it cites.
OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2024 · 2024
Later among the works it cites.
Mitigating hallucinations and off-target machine translation with source-contrastive and language-contrastive decoding
Rico Sennrich, Jannis Vamvas, and Alireza Mohammadshahi. 2024 · 2024
Later among the works it cites.
A comprehensive survey of hallucination mitigation techniques in large language models
S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, Anku Rani, Vipula Rawte, Aman Chadha, and Amitava Das. 2024 · 2024
Later among the works it cites.
Contrastive preference optimization: Pushing the boundaries of LLM performance in machine translation
Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kenton Murray, and Young Jin Kim. 2024 · 2024
Later among the works it cites.