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Multitask prompted finetuning (MTF) has been shown to help large language models generalize to new tasks in a zero-shot setting, but so far explorations of MTF have focused on English data and models.
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, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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Paws: Paraphrase adversaries from word scrambling
Yuan Zhang, Jason Baldridge, and Luheng He. 2019 · 1904
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Neural code search evaluation dataset
2018 · 1908
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On the cross-lingual transferability of monolingual representations
Mikel Artetxe, Sebastian Ruder, and Dani Yogatama. 2019 · 1910
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Mlqa: Evaluating cross-lingual extractive question answering
Patrick Lewis, Barlas Oguz, Ruty Rinott, Sebastian Riedel, and Holger Schwenk. 2019 · 1910
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Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1911
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Binary codes capable of correcting deletions, insertions, and reversals
Vladimir I Levenshtein et al. 1966 · 1966
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Exploiting cloze questions for few shot text classification and natural language inference
Timo Schick and Hinrich Schütze. 2020 · 2001
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Exploiting cloze questions for few-shot text classification and natural language inference
Timo Schick and Hinrich Schütze. 2020 · 2001
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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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Clue: A chinese language understanding evaluation benchmark
Liang Xu, Hai Hu, Xuanwei Zhang, Lu Li, Chenjie Cao, Yudong Li, Yechen Xu, Kai Sun, Dian Yu, Cong Yu, et al. 2020 · 2004
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English intermediate-task training improves zero-shot cross-lingual transfer too
Jason Phang, Iacer Calixto, Phu Mon Htut, Yada Pruksachatkun, Haokun Liu, Clara Vania, Katharina Kann, and Samuel R Bowman. 2020 · 2005
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Wikilingua: A new benchmark dataset for multilingual abstractive summarization
2020 · 2010
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mt5: A massively multilingual pre-trained text-to-text transformer
Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, and Colin Raffel. 2020 · 2010
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Choice of plausible alternatives: An evaluation of commonsense causal reasoning
Melissa Roemmele, Cosmin Adrian Bejan, and Andrew S Gordon. 2011 · 2011
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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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Xnli: Evaluating cross-lingual sentence representations
Alexis Conneau, Ruty Rinott, Guillaume Lample, Adina Williams, Samuel R. Bowman, Holger Schwenk, and Veselin Stoyanov. 2018 · 2018
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A span-extraction dataset for chinese machine reading comprehension
Yiming Cui, Ting Liu, Li Xiao, Zhipeng Chen, Wentao Ma, Wanxiang Che, Shijin Wang, and Guoping Hu. 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. 2018 · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
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Two new evaluation datasets for low-resource machine translation: Nepali-english and sinhala-english
Francisco Guzm’an, Peng-Jen Chen, Myle Ott, Juan Pino, Guillaume Lample, Philipp Koehn, Vishrav Chaudhary, and Marc’Aurelio Ranzato. 2019 · 2019
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Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau. 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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Beto, bentz, becas: The surprising cross-lingual effectiveness of BERT
Shijie Wu and Mark Dredze. 2019 · 2019
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PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification
Yinfei Yang, Yuan Zhang, Chris Tar, and Jason Baldridge. 2019 · 2019
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Global relational models of source code
Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, and David Bieber. 2020 · 2020
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Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
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XCOPA: A multilingual dataset for causal commonsense reasoning
Edoardo M. Ponti, Goran Glavas, Olga Majewska, Qianchu Liu, Ivan Vuli’c, and Anna Korhonen. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J Liu, et al. 2020 · 2020
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Xl-wic: A multilingual benchmark for evaluating semantic contextualization
Alessandro Raganato, Tommaso Pasini, Jose Camacho-Collados, and Mohammad Taher Pilehvar. 2020 · 2020
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Investigating prior knowledge for challenging chinese machine reading comprehension
Kai Sun, Dian Yu, Dong Yu, and Claire Cardie. 2020 · 2020
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The Tatoeba Translation Challenge – Realistic data sets for low resource and multilingual MT
J"org Tiedemann. 2020 · 2020
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Ext5: Towards extreme multi-task scaling for transfer learning
Vamsi Aribandi, Yi Tay, Tal Schuster, Jinfeng Rao, Huaixiu Steven Zheng, Sanket Vaibhav Mehta, Honglei Zhuang, Vinh Q. Tran, Dara Bahri, Jianmo Ni, Jai Prakash Gupta, Kai Hui, Sebastian Ruder, and Donald Metzler. 2021 · 2021
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Program synthesis with large language models
Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, et al. 2021 · 2021
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Gpt-neo: Large scale autoregressive language modeling with mesh-tensorflow
Sid Black, Leo Gao, Phil Wang, Connor Leahy, and Stella Biderman. 2021 · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al. 2021 · 2021
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Ilias Chalkidis, Manos Fergadiotis, and Ion Androutsopoulos. 2021 · 2021
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Evaluating large language models trained on code
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The bigscience roots corpus: A 1.6 tb composite multilingual dataset
Hugo Laurençon, Lucile Saulnier, Thomas Wang, Christopher Akiki, Albert Villanova del Moral, Teven Le Scao, Leandro Von Werra, Chenghao Mou, Eduardo González Ponferrada, Huu Nguyen, et al. 2022 · 2022
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Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
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Sgpt: Gpt sentence embeddings for semantic search
Niklas Muennighoff. 2022 · 2022
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Mteb: Massive text embedding benchmark
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No language left behind: Scaling human-centered machine translation
NLLB Team, Marta R. Costa-jussà, 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
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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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A framework for few-shot language model evaluation
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XL-sum: Large-scale multilingual abstractive summarization for 44 languages
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Measuring coding challenge competence with apps
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Lora: Low-rank adaptation of large language models
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BiSECT: Learning to split and rephrase sentences with bitexts
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Packing: Towards 2x nlp bert acceleration
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Bidirectional language models are also few-shot learners
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Multitask prompted training enables zero-shot task generalization
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Continual-t0: Progressively instructing 50+ tasks to language models without forgetting
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mgpt: Few-shot learners go multilingual
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