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Contrastive learning is emerging as a powerful technique for extracting knowledge from unlabeled data.
Representation degeneration problem in training natural language generation models
Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, and Tie-Yan Liu. 2019 · 1907
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Cert: Contrastive self-supervised learning for language understanding
Hongchao Fang and Pengtao Xie. 2020 · 2005
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Dimensionality reduction by learning an invariant mapping
R. Hadsell, S. Chopra, and Y. LeCun. 2006 · 2006
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Semeval-2012 task 6: A pilot on semantic textual similarity
Eneko Agirre, Daniel Cer, Mona Diab, and Aitor Gonzalez-Agirre. 2012 · 2012
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Clear: Contrastive learning for sentence representation
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*sem 2013 shared task: Semantic textual similarity
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Semeval-2014 task 10: Multilingual semantic textual similarity
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GloVe: Global vectors for word representation
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Semeval-2015 task 2: Semantic textual similarity, english, spanish and pilot on interpretability
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Inigo Lopez-Gazpio, Montse Maritxalar, Rada Mihalcea, German Rigau, Larraitz Uria, and Janyce Wiebe. 2015 · 2015
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Explaining and harnessing adversarial examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy. 2015 · 2015
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Semeval-2016 task 1: Semantic textual similarity, monolingual and cross-lingual evaluation
Eneko Agirre, Carmen Banea, Daniel M. Cer, Mona T. Diab, Aitor Gonzalez-Agirre, Rada Mihalcea, German Rigau, and Janyce Wiebe. 2016 · 2016
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Semeval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel M. Cer, Mona T. Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 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 N. Toutanova. 2018 · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020 · 2020
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Bootstrap your own latent: A new approach to self-supervised learning
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick. 2020 · 2020
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Contrastive learning with adversarial examples
Chih-Hui Ho and Nuno Nvasconcelos. 2020 · 2020
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Jigsaw clustering for unsupervised visual representation learning
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Exploring simple siamese representation learning
Xinlei Chen and Kaiming He. 2021 · 2021
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Whitening for self-supervised representation learning
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Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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DeCLUTR: Deep contrastive learning for unsupervised textual representations
John Giorgi, Osvald Nitski, Bo Wang, and Gary Bader. 2021 · 2021
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huggingface/datasets: 1.13.2
Quentin Lhoest, Albert Villanova del Moral, Patrick von Platen, Thomas Wolf, Yacine Jernite, Abhishek Thakur, Lewis Tunstall, Suraj Patil, Mariama Drame, Julien Chaumond, Julien Plu, Joe Davison, Simon Brandeis, Victor Sanh, Teven Le Scao, Kevin Canwen Xu, Nicolas Patry, Steven Liu, Angelina McMillan-Major, Philipp Schmid, Sylvain Gugger, Nathan Raw, Sylvain Lesage, Anton Lozhkov, Matthew Carrigan, Théo Matussière, Leandro von Werra, Lysandre Debut, Stas Bekman, and Clément Delangue. 2021 · 2021
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On the sentence embeddings from pre-trained language models
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Less can be more in contrastive learning
Jovana Mitrovic, Brian McWilliams, and Melanie Rey. 2020 · 2020
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Understanding contrastive representation learning through alignment and uniformity on the hypersphere
Tongzhou Wang and Phillip Isola. 2020 · 2020
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Transformers: State-of-the-art natural language processing
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An unsupervised sentence embedding method by mutual information maximization
Yan Zhang, Ruidan He, Zuozhu Liu, Kwan Hui Lim, and Lidong Bing. 2020a · 2020
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Revisiting representation degeneration problem in language modeling
Zhong Zhang, Chongming Gao, Cong Xu, Rui Miao, Qinli Yang, and Junming Shao. 2020b · 2020
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Semantic re-tuning with contrastive tension
Fredrik Carlsson, Magnus Sahlgren, Evangelia Gogoulou, Amaru Cuba Gyllensten, and Erik Ylipää Hellqvist. 2021 · 2021
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Prototypical contrastive learning of unsupervised representations
Junnan Li, Pan Zhou, Caiming Xiong, and Steven Hoi. 2021 · 2021
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Whitening sentence representations for better semantics and faster retrieval
Jianlin Su, Jiarun Cao, Weijie Liu, and Yangyiwen Ou. 2021 · 2021
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Cline: Contrastive learning with semantic negative examples for natural language understanding
Dong Wang, Ning Ding, Piji Li, and Haitao Zheng. 2021 · 2021
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Sick-nl: A dataset for dutch natural language inference
Gijs Wijnholds and Michael Moortgat. 2021 · 2021
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Consert: A contrastive framework for self-supervised sentence representation transfer
Yuanmeng Yan, Rumei Li, Sirui Wang, Fuzheng Zhang, Wei Wu, and Weiran Xu. 2021 · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, yann lecun, and Stephane Deny. 2021 · 2021
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