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Publicly available clinical BERT embeddings
Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, and Matthew B. A. McDermott. 2019 · 1904
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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 · 1910
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On measures of entropy and information
Alfréd Rényi. 1961 · 1961
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Ohio supercomputer center
OSC. 1987 · 1987
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Differential privacy
Cynthia Dwork. 2006 · 2006
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Mechanism design via differential privacy
Frank McSherry and Kunal Talwar. 2007 · 2007
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Wikicorpus: A word-sense disambiguated multilingual wikipedia corpus
Samuel Reese, Gemma Boleda, Montse Cuadros, Lluís Padró, and German Rigau. 2010 · 2010
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An attack on InstaHide: Is private learning possible with instance encoding?
Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Shuang Song, Abhradeep Thakurta, and Florian Tramèr. 2020a · 2011
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Extracting training data from large language models
Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel. 2020b · 2012
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Geo-indistinguishability: differential privacy for location-based systems
Miguel E. Andrés, Nicolás Emilio Bordenabe, Konstantinos Chatzikokolakis, and Catuscia Palamidessi. 2013 · 2013
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Broadening the scope of differential privacy using metrics
Konstantinos Chatzikokolakis, Miguel E. Andrés, Nicolás Emilio Bordenabe, and Catuscia Palamidessi. 2013 · 2013
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Local privacy and statistical minimax rates
John C. Duchi, Michael I. Jordan, and Martin J. Wainwright. 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 Y. Ng, and Christopher Potts. 2013 · 2013
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
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Only you, your doctor, and many others may know
Latanya Sweeney. 2015 · 2015
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Plausible deniability for privacy-preserving data synthesis
Vincent Bindschaedler, Reza Shokri, and Carl A. Gunter. 2017 · 2017
Cited alongside, same era.
Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017 · 2017
Cited alongside, same era.
Locally differentially private protocols for frequency estimation
Tianhao Wang, Jeremiah Blocki, Ninghui Li, and Somesh Jha. 2017 · 2017
Cited alongside, same era.
Controllable invariance through adversarial feature learning
Qizhe Xie, Zihang Dai, Yulun Du, Eduard H. Hovy, and Graham Neubig. 2017 · 2017
Cited alongside, same era.
Local differential privacy on metric spaces: Optimizing the trade-off with utility
Mário S. Alvim, Konstantinos Chatzikokolakis, Catuscia Palamidessi, and Anna Pazii. 2018 · 2018
Cited alongside, same era.
Privacy-preserving neural representations of text
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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Slalom: Fast, verifiable and private execution of neural networks in trusted hardware
Florian Tramèr and Dan Boneh. 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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Privacy- and utility-preserving textual analysis via calibrated multivariate perturbations
Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, and Tom Diethe. 2020 · 2020
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TextHide: Tackling data privacy for language understanding tasks
Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, and Sanjeev Arora. 2020 · 2020
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Maximin Coavoux, Shashi Narayan, and Shay B. Cohen. 2018 · 2018
Cited alongside, same era.
Marginal release under local differential privacy
Graham Cormode, Tejas Kulkarni, and Divesh Srivastava. 2018 · 2018
Cited alongside, same era.
Adversarial removal of demographic attributes from text data
Yanai Elazar and Yoav Goldberg. 2018 · 2018
Cited alongside, same era.
Towards robust and privacy-preserving text representations
Yitong Li, Timothy Baldwin, and Trevor Cohn. 2018 · 2018
Cited alongside, same era.
Learning differentially private recurrent language models
H. Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang. 2018 · 2018
Cited alongside, same era.
Locally differentially private frequent itemset mining
Tianhao Wang, Ninghui Li, and Somesh Jha. 2018 · 2018
Cited alongside, same era.
SynTF: Synthetic and differentially private term frequency vectors for privacy-preserving text mining
Benjamin Weggenmann and Florian Kerschbaum. 2018 · 2018
Cited alongside, same era.
Qian Lou, Bo Feng, Geoffrey Charles Fox, and Lei Jiang. 2020 · 2020
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Privacy risks of general-purpose language models
Xudong Pan, Mi Zhang, Shouling Ji, and Min Yang. 2020 · 2020
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Information leakage in embedding models
Congzheng Song and Ananth Raghunathan. 2020 · 2020
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MedSTS: a resource for clinical semantic textual similarity
Yanshan Wang, Naveed Afzal, Sunyang Fu, Liwei Wang, Feichen Shen, Majid Rastegar-Mojarad, and Hongfang Liu. 2020 · 2020
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Learning model with error - exposing the hidden model of BAYHENN
Harry W. H. Wong, Jack P. K. Ma, Donald P. H. Wong, Lucien K. L. Ng, and Sherman S. M. Chow. 2020 · 2020
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GForce: GPU-friendly oblivious and rapid neural network inference
Lucien K. L. Ng and Sherman S. M. Chow. 2021 · 2021
Closest in time.
Goten: GPU-Outsourcing Trusted Execution of Neural Network Training
Lucien K. L. Ng, Sherman S. M. Chow, Anna P. Y. Woo, Donald P. H. Wong, and Yongjun Zhao. 2021 · 2021
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Privacy-adaptive BERT for natural language understanding
Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky, and Marc Najork. 2021 · 2021
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FALCON: Honest-majority maliciously secure framework for private deep learning
Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, and Tal Rabin. 2021 · 2021
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