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Generative Large Language Models (LLMs) have achieved remarkable advancements in various NLP tasks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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On the origin of the early indian scripts
Richard Salomon. 1995 · 1995
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, and Pascal Vincent. 2000 · 2000
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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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Statistical language model adaptation: review and perspectives
Jerome R Bellegarda. 2004 · 2004
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chrf: character n-gram f-score for automatic mt evaluation
Maja Popović. 2015 · 2015
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Exploring massively multilingual, massive neural machine translation
Ankur Bapna and Orhan Firat. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Proceedings of the Fifth Conference on Machine Translation . Association for Computational Linguistics, Online
Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, and Matteo Negri, editors. 2020 · 2020
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A survey of multilingual neural machine translation
Raj Dabre, Chenhui Chu, and Anoop Kunchukuttan. 2020 · 2020
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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. 2021 · 2021
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A survey on low-resource neural machine translation
Rui Wang, Xu Tan, Renqian Luo, Tao Qin, and Tie-Yan Liu. 2021 · 2021
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Language as an interstate migration barrier–the interesting case of india
Jakub Zieliński et al. 2021 · 2021
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Building multilingual machine translation systems that serve arbitrary xy translations
Akiko Eriguchi, Shufang Xie, Tao Qin, and Hany Hassan Awadalla. 2022 · 2022
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NTREX-128 – news test references for MT evaluation of 128 languages
Christian Federmann, Tom Kocmi, and Ying Xin. 2022 · 2022
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The Flores-101 evaluation benchmark for low-resource and multilingual machine translation
Naman Goyal, Cynthia Gao, Vishrav Chaudhary, Peng-Jen Chen, Guillaume Wenzek, Da Ju, Sanjana Krishnan, Marc’Aurelio Ranzato, Francisco Guzmán, and Angela Fan. 2022 · 2022
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Peft: State-of-the-art parameter-efficient fine-tuning methods
Sourab Mangrulkar, Sylvain Gugger, Lysandre Debut, Younes Belkada, Sayak Paul, and Benjamin Bossan. 2022 · 2022
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COMET-22: Unbabel-IST 2022 submission for the metrics shared task
Ricardo Rei, José G. C. de Souza, Duarte Alves, Chrysoula Zerva, Ana C Farinha, Taisiya Glushkova, Alon Lavie, Luisa Coheur, and André F. T. Martins. 2022 · 2022
Jay Gala, Pranjal A Chitale, Raghavan AK, Sumanth Doddapaneni, Varun Gumma, Aswanth Kumar, Janki Nawale, Anupama Sujatha, Ratish Puduppully, Vivek Raghavan, et al. 2023 · 2023
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Hallucinations in large multilingual translation models
Nuno M Guerreiro, Duarte Alves, Jonas Waldendorf, Barry Haddow, Alexandra Birch, Pierre Colombo, and André FT Martins. 2023 · 2023
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Making instruction finetuning accessible to non-English languages: A case study on Swedish models
Oskar Holmström and Ehsan Doostmohammadi. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
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Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al. 2022 · 2022
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Overcoming language barriers in academia: Machine translation tools and a vision for a multilingual future
Emma Steigerwald, Valeria Ramírez-Castañeda, Débora YC Brandt, András Báldi, Julie Teresa Shapiro, Lynne Bowker, and Rebecca D Tarvin. 2022 · 2022
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Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models
Priyan Vaithilingam, Tianyi Zhang, and Elena L Glassman. 2022 · 2022
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Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2022
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AI4Bharat, Jay Gala, Pranjal A. Chitale, Raghavan AK, Sumanth Doddapaneni, Varun Gumma, Aswanth Kumar, Janki Nawale, Anupama Sujatha, Ratish Puduppully, Vivek Raghavan, Pratyush Kumar, Mitesh M. Khapra, Raj Dabre, and Anoop Kunchukuttan. 2023 · 2023
Cited alongside, same era.
Characterizing attribution and fluency tradeoffs for retrieval-augmented large language models
Renat Aksitov, Chung-Ching Chang, David Reitter, Siamak Shakeri, and Yunhsuan Sung. 2023 · 2023
Cited alongside, same era.
Falcon-40b: an open large language model with state-of-the-art performance
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Merouane Debbah, Etienne Goffinet, Daniel Heslow, Julien Launay, Quentin Malartic, et al. 2023 · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
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Viet Dac Lai, Nghia Trung Ngo, Amir Pouran Ben Veyseh, Hieu Man, Franck Dernoncourt, Trung Bui, and Thien Huu Nguyen. 2023 · 2023
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A comprehensive overview of large language models
Humza Naveed, Asad Ullah Khan, Shi Qiu, Muhammad Saqib, Saeed Anwar, Muhammad Usman, Nick Barnes, and Ajmal Mian. 2023 · 2023
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Neural machine translation models can learn to be few-shot learners
Raphael Reinauer, Patrick Simianer, Kaden Uhlig, Johannes EM Mosig, and Joern Wuebker. 2023 · 2023
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The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al. 2023 · 2023
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A paradigm shift in machine translation: Boosting translation performance of large language models
Haoran Xu, Young Jin Kim, Amr Sharaf, and Hany Hassan Awadalla. 2023 · 2023
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A systematic evaluation of large language models for natural
Ni Xuanfan and Li Piji. 2023 · 2023
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Prompting large language model for machine translation: A case study
Biao Zhang, Barry Haddow, and Alexandra Birch. 2023 · 2023
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Multilingual machine translation with large language models: Empirical results and analysis
Wenhao Zhu, Hongyi Liu, Qingxiu Dong, Jingjing Xu, Lingpeng Kong, Jiajun Chen, Lei Li, and Shujian Huang. 2023 · 2023
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Reliable and safe use of machine translation in medical settings
Nikita Mehandru, Samantha Robertson, and Niloufar Salehi. 2022 · 2025
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