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This paper presents a novel training method, Conditional Masked Language Modeling (CMLM), to effectively learn sentence representations on large scale unlabeled corpora.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Multilingual universal sentence encoder for semantic retrieval
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Seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales
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Language-agnostic bert sentence embedding
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Cross-language text classification using structural correspondence learning
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts. 2013 · 2013
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A sick cure for the evaluation of compositional distributional semantic models
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Russ R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
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Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, et al. 2018 · 2018
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Senteval: An evaluation toolkit for universal sentence representations
Alexis Conneau and Douwe Kiela. 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. 2019 · 2019
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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, and Peter J. Liu. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Unsupervised cross-lingual representation learning
Sebastian Ruder, Anders Søgaard, and Ivan Vulić. 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. 2019c · 2019
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An efficient framework for learning sentence representations
Lajanugen Logeswaran and Honglak Lee. 2018 · 2018
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Learning general purpose distributed sentence representations via large scale multi-task learning
Sandeep Subramanian, Adam Trischler, Yoshua Bengio, and Christopher J Pal. 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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Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond
Mikel Artetxe and Holger Schwenk. 2019 · 2019
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Learning cross-lingual sentence representations via a multi-task dual-encoder model
Muthu Chidambaram, Yinfei Yang, Daniel Cer, Steve Yuan, Yunhsuan Sung, Brian Strope, and Ray Kurzweil. 2019 · 2019
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Improving multilingual sentence embedding using bi-directional dual encoder with additive margin softmax
Yinfei Yang, Gustavo Hernandez Abrego, Steve Yuan, Mandy Guo, Qinlan Shen, Daniel Cer, Yun-hsuan Sung, Brian Strope, and Ray Kurzweil. 2019b
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Parameter-free sentence embedding via orthogonal basis
Ziyi Yang, Chenguang Zhu, and Weizhu Chen. 2019e · 2019
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ETC: Encoding long and structured inputs in transformers
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Albert: A lite bert for self-supervised learning of language representations
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Kumar Avinava Dubey Joshua Ainslie Chris Alberti Santiago Ontanon Philip Pham Anirudh Ravula Qifan Wang Li Yang Amr Ahmed Manzil Zaheer, Guru Guruganesh. 2020 · 2020
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Large batch optimization for deep learning: Training bert in 76 minutes
Yang You, Jing Li, Sashank Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojanapalli, Xiaodan Song, James Demmel, Kurt Keutzer, and Cho-Jui Hsieh. 2020 · 2020
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