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Sentence embeddings are an important component of many natural language processing (NLP) systems.
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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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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Triplet-center loss for multi-view 3d object retrieval
Xinwei He, Yang Zhou, Zhichao Zhou, Song Bai, and Xiang Bai. 2018 · 1954
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen. 1989 · 1989
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Roger Ratcliff. 1990 · 1990
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Similarity metric learning for a variable-kernel classifier
David G Lowe. 1995 · 1995
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Fisher discriminant analysis with kernels
Sebastian Mika, Gunnar Ratsch, Jason Weston, Bernhard Scholkopf, and Klaus-Robert Mullers. 1999 · 1999
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Building a question answering test collection
Ellen M Voorhees and Dawn M Tice. 2000 · 2000
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Distance metric learning with application to clustering with side-information
Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, and Stuart J. Russell. 2002 · 2002
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Unsupervised construction of large paraphrase corpora: Exploiting massively parallel news sources
Bill Dolan, Chris Quirk, and Chris Brockett. 2004 · 2004
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Mining and summarizing customer reviews
Minqing Hu and Bing Liu. 2004 · 2004
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A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
Bo Pang and Lillian Lee. 2004 · 2004
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Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee. 2005 · 2005
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Annotating expressions of opinions and emotions in language
Janyce Wiebe, Theresa Wilson, and Claire Cardie. 2005 · 2005
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Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann 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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*sem 2013 shared task: Semantic textual similarity
Eneko Agirre, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, and Weiwei Guo. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
Tomás Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, and Jeffrey Dean. 2013 · 2013
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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 Ng, and Christopher Potts. 2013 · 2013
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SemEval-2014 task 10: Multilingual semantic textual similarity
Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Rada Mihalcea, German Rigau, and Janyce Wiebe. 2014 · 2014
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Distributed representations of sentences and documents
Quoc V. Le and Tomás Mikolov. 2014 · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
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A SICK cure for the evaluation of compositional distributional semantic models
Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, and Roberto Zamparelli. 2014 · 2014
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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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, Iñigo Lopez-Gazpio, Montse Maritxalar, Rada Mihalcea, German Rigau, Larraitz Uria, and Janyce Wiebe. 2015 · 2015
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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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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Learning descriptors for object recognition and 3d pose estimation
Paul Wohlhart and Vincent Lepetit. 2015 · 2015
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SemEval-2016 task 1: Semantic textual similarity, monolingual and cross-lingual evaluation
Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Rada Mihalcea, German Rigau, and Janyce Wiebe. 2016 · 2016
Cited alongside, same era.
Improving semantic embedding consistency by metric learning for zero-shot classiffication
Maxime Bucher, Stéphane Herbin, and Frédéric Jurie. 2016 · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Cited alongside, same era.
Learning distributed representations of sentences from unlabelled data
Felix Hill, Kyunghyun Cho, and Anna Korhonen. 2016 · 2016
Cited alongside, same era.
Learning by tracking: Siamese cnn for robust target association
Laura Leal-Taixé, Cristian Canton-Ferrer, and Konrad Schindler. 2016 · 2016
Cited alongside, same era.
Improved deep metric learning with multi-class n-pair loss objective
Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X. Yu, and Dahua Lin. 2018 · 2018
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A zero-shot framework for sketch based image retrieval
Sasi Kiran Yelamarthi, Shiva Krishna Reddy, Ashish Mishra, and Anurag Mittal. 2018 · 2018
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Hard-aware point-to-set deep metric for person re-identification
Rui Yu, Zhiyong Dou, Song Bai, Zhaoxiang Zhang, Yongchao Xu, and Xiang Bai. 2018 · 2018
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Learning representations by maximizing mutual information across views
Philip Bachman, R. Devon Hjelm, and William Buchwalter. 2019 · 2019
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Cross-lingual language model pretraining
Alexis Conneau and Guillaume Lample. 2019 · 2019
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Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov. 2019 · 2019
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Kihyuk Sohn. 2016 · 2016
Cited alongside, same era.
Siamese instance search for tracking
Ran Tao, Efstratios Gavves, and Arnold W. M. Smeulders. 2016 · 2016
Cited alongside, same era.
A discriminative feature learning approach for deep face recognition
Yandong Wen, Kaipeng Zhang, Zhifeng Li, and Yu Qiao. 2016 · 2016
Cited alongside, same era.
Zero-shot learning via joint latent similarity embedding
Ziming Zhang and Venkatesh Saligrama. 2016 · 2016
Cited alongside, same era.
SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Efficient natural language response suggestion for smart reply
Matthew Henderson, Rami Al-Rfou, Brian Strope, Yun-Hsuan Sung, László Lukács, Ruiqi Guo, Sanjiv Kumar, Balint Miklos, and Ray Kurzweil. 2017 · 2017
Cited alongside, same era.
Later among the works it cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Later among the works it cites.
Openwebtext corpus
Aaron Gokaslan and Vanya Cohen. 2019 · 2019
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Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, and Yoshua Bengio. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Pytorch metric learning
Kevin Musgrave, Ser-Nam Lim, and Serge Belongie. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 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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Transfer learning in natural language processing
Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, and Thomas Wolf. 2019 · 2019
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A theoretical analysis of contrastive unsupervised representation learning
Nikunj Saunshi, Orestis Plevrakis, Sanjeev Arora, Mikhail Khodak, and Hrishikesh Khandeparkar. 2019 · 2019
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 2019
Later among the works it cites.
Reducing bert pre-training time from 3 days to 76 minutes. corr abs/1904.00962 (2019)
Yang You, Jing Li, Jonathan Hseu, Xiaodan Song, James Demmel, and C Hsieh. 1904 · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020 · 2020
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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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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross B. Girshick. 2020 · 2020
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SpanBERT: Improving pre-training by representing and predicting spans
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S. Weld, Luke Zettlemoyer, and Omer Levy. 2020 · 2020
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A mutual information maximization perspective of language representation learning
Lingpeng Kong, Cyprien de Masson d’Autume, Lei Yu, Wang Ling, Zihang Dai, and Dani Yogatama. 2020 · 2020
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ALBERT: A lite BERT for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
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Contrastive multiview coding
Yonglong Tian, Dilip Krishnan, and Phillip Isola. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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In defense of the triplet loss again: Learning robust person re-identification with fast approximated triplet loss and label distillation
Ye Yuan, Wuyang Chen, Yang Yang, and Zhangyang Wang. 2020 · 2020
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