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The recent advances in natural language processing have predominantly favored well-resourced English-centric models, resulting in a significant gap with low-resource languages.
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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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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KenLM: Faster and smaller language model queries
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Parallel data, tools and interfaces in OPUS
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
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Decoupled weight decay regularization
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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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Words, meanings, characters in sentiment analysis
Mehmet Fatih Amasyali, Hakan Tasköprü, and Kübra Çaliskan. 2018 · 2018
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Subword regularization: Improving neural network translation models with multiple subword candidates
Taku Kudo. 2018 · 2018
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SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
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OpenSubtitles2018: Statistical rescoring of sentence alignments in large, noisy parallel corpora
Pierre Lison, Jörg Tiedemann, and Milen Kouylekov. 2018 · 2018
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Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern. 2018 · 2018
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Implementing universal dependency, morphology, and multiword expression annotation standards for turkish language processing
Umut Sulubacak and Gülşen Eryiğit. 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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A comparative analysis of text classification for turkish language
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Multilingual language models for named entity recognition in German and English
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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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Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019 · 2019
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Language models are unsupervised multitask learners
Semantic similarity based evaluation for abstractive news summarization
Figen Beken Fikri, Kemal Oflazer, and Berrin Yanikoglu. 2021 · 2021
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How good is your tokenizer? on the monolingual performance of multilingual language models
Phillip Rust, Jonas Pfeiffer, Ivan Vulić, Sebastian Ruder, and Iryna Gurevych. 2021 · 2021
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EstBERT: A pretrained language-specific BERT for Estonian
Hasan Tanvir, Claudia Kittask, Sandra Eiche, and Kairit Sirts. 2021 · 2021
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Scale efficiently: Insights from pre-training and fine-tuning transformers
Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, and Donald Metzler. 2021 · 2021
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mT5: A massively multilingual pre-trained text-to-text transformer
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Massively multilingual transfer for NER
Afshin Rahimi, Yuan Li, and Trevor Cohn. 2019 · 2019
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Data and Representation for Turkish Natural Language Inference
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ELECTRA: pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
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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. 2020 · 2020
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Convbert: Improving bert with span-based dynamic convolution
Zi-Hang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, and Shuicheng Yan. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Towards a Cleaner Document-Oriented Multilingual Crawled Corpus
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Semantic similarity based filtering for Turkish paraphrase dataset creation
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Abstractive text summarization and new large-scale datasets for agglutinative languages turkish and hungarian
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Few-shot learning with multilingual generative language models
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mgpt: Few-shot learners go multilingual
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Galactica: A large language model for science
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An exploration of encoder-decoder approaches to multi-label classification for legal and biomedical text
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Ud turkish boun
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Scaling data-constrained language models
Niklas Muennighoff, Alexander M Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, and Colin Raffel. 2023 · 2023
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Unifying language learning paradigms
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Llama: Open and efficient foundation language models
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Ud turkish imst
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