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Deep Neural Network (DNN) models have been shown to have high empirical privacy leakages.
Scibert: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 1903
Earlier work this paper cites.
Publicly available clinical bert embeddings
Emily Alsentzer, John R Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, and Matthew McDermott. 2019 · 1904
Earlier work this paper cites.
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
Earlier work this paper cites.
Resolving individuals contributing trace amounts of dna to highly complex mixtures using high-density snp genotyping microarrays
Nils Homer, Szabolcs Szelinger, Margot Redman, David Duggan, Waibhav Tembe, Jill Muehling, John V Pearson, Dietrich A Stephan, Stanley F Nelson, and David W Craig. 2008 · 2008
Earlier work this paper cites.
Robust de-anonymization of large sparse datasets
Arvind Narayanan and Vitaly Shmatikov. 2008 · 2008
Earlier work this paper cites.
Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al. 2020 · 2012
Earlier work this paper cites.
The algorithmic foundations of differential privacy
Cynthia Dwork, Aaron Roth, et al. 2014 · 2014
Earlier work this paper cites.
Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang. 2016 · 2016
Earlier work this paper cites.
Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, H Lehman Li-Wei, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark. 2016 · 2016
Cited alongside, same era.
Rényi differential privacy
Ilya Mironov. 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.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 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.
Privacy risk in machine learning: Analyzing the connection to overfitting
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha. 2018 · 2018
Later among the works it cites.
Evaluating differentially private machine learning in practice
Bargav Jayaraman and David Evans. 2019 · 2019
Later among the works it cites.
Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning
Milad Nasr, Reza Shokri, and Amir Houmansadr. 2019 · 2019
Later among the works it cites.
Transfer learning in biomedical natural language processing: An evaluation of bert and elmo on ten benchmarking datasets
Yifan Peng, Shankai Yan, and Zhiyong Lu. 2019 · 2019
Later among the works it cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Later among the works it cites.
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Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Úlfar Erlingsson. 2018 · 2018
Cited alongside, same era.
Lessons from natural language inference in the clinical domain
Alexey Romanov and Chaitanya Shivade. 2018 · 2018
Cited alongside, same era.
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. 2018 · 2018
Cited alongside, same era.
Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 2019 · 2019
Later among the works it cites.
Membership inference attacks on sequence-to-sequence models: Is my data in your machine translation system?
Sorami Hisamoto, Matt Post, and Kevin Duh. 2020 · 2020
Later among the works it cites.
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2020 · 2020
Later among the works it cites.