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Natural language reflects our private lives and identities, making its privacy concerns as broad as those of real life.
Logic and conversation
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Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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Neural CRF parsing
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Algorithmically Bypassing Censorship on Sina Weibo with Nondeterministic Homophone Substitutions
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Deep learning with differential privacy
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About the Panama Papers investigations
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Mimic-iii, a freely accessible critical care database
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A persona-based neural conversation model
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De-identification of patient notes with recurrent neural networks
Franck Dernoncourt, Ji Young Lee, Ozlem Uzuner, and Peter Szolovits · 2017
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Towards measuring membership privacy
Yunhui Long, Vincent Bindschaedler, and Carl A. Gunter · 2017
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Learning differentially private language models without losing accuracy
H Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang · 2017
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Membership inference attacks against machine learning models
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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#MeToo Alexa: How conversational systems respond to sexual harassment
Amanda Cercas Curry and Verena Rieser · 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 · 2018
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Ethical challenges in data-driven dialogue systems
Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, and Joelle Pineau · 2018
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Ahmed Salem, Yang Zhang, Mathias Humbert, Mario Fritz, and Michael Backes · 2018
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The natural auditor: How to tell if someone used your words to train their model
Congzheng Song and Vitaly Shmatikov · 2018
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Evaluation of a sequence tagging tool for biomedical texts
Julien Tourille, Matthieu Doutreligne, Olivier Ferret, Aurélie Névéol, Nicolas Paris, and Xavier Tannier · 2018
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Self-contained system for de-identifying unstructured data in healthcare records, August 1 2019
Joseph Austin, Shahir Kassam-Adams, Jason A LaBonte, and Paul J Bayless · 2019
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Gmail smart compose: Real-time assisted writing
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Understanding database reconstruction attacks on public data
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Knowledge is power: Prior knowledge aids memory for both congruent and incongruent events, but in different ways
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Analyzing Information Leakage of Updates to Natural Language Models
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Large-scale differentially private bert
Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, and Pasin Manurangsi · 2021
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Protecting personally identifiable information (pii) using tagging and persistence of pii, January 5 2021
Andreas Balzer, David Mowatt, and Muiris Woulfe · 2021
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On the dangers of stochastic parrots: Can language models be too big?
Emily M Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell · 2021
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GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow
Sid Black, Leo Gao, Phil Wang, Connor Leahy, and Stella Biderman · 2021
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Bridget Haire, Christy E. Newman, and Bianca Fileborn · 2019
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Generalization through memorization: Nearest neighbor language models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis · 2019
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Ai dungeon, 2019
Latitude · 2019
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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
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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
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Specaugment: A simple data augmentation method for automatic speech recognition
Daniel S Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D Cubuk, and Quoc V Le · 2019
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Language models are unsupervised multitask learners
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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Differential privacy dynamics of langevin diffusion and noisy gradient descent
Rishav Chourasia, Jiayuan Ye, and Reza Shokri · 2021
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Documenting the english colossal clean crawled corpus
Jesse Dodge, Maarten Sap, Ana Marasović, William Agnew, Gabriel Ilharco, Dirk Groeneveld, and Matt Gardner · 2021
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Management systems for personal identifying data, and methods relating thereto, January 12 2021
Jennifer L Donovan, Gary Adler, and James Holladay · 2021
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Utility-preserving text de-identification with privacy guarantees, October 28 2021
Aris Gkoulalas-Divanis, Paul R Bastide, Xu Wang, and Rohit Ranchal · 2021
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Pre-trained models: Past, present and future
Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, and Jun Zhu · 2021
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Learning and evaluating a differentially private pre-trained language model
Shlomo Hoory, Amir Feder, Avichai Tendler, Alon Cohen, Sofia Erell, Itay Laish, Hootan Nakhost, Uri Stemmer, Ayelet Benjamini, Avinatan Hassidim, et al · 2021
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The importance of modeling social factors of language: Theory and practice
Dirk Hovy and Diyi Yang · 2021
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Delphi: Towards machine ethics and norms
Liwei Jiang, Jena D Hwang, Chandra Bhagavatula, Ronan Le Bras, Maxwell Forbes, Jon Borchardt, Jenny Liang, Oren Etzioni, Maarten Sap, and Yejin Choi · 2021
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Trkic G00gle: Why and How Users Game Translation Algorithms
Soomin Kim, Changhoon Oh, Won Ik Cho, Donghoon Shin, Bongwon Suh, and Joonhwan Lee · 2021
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Deduplicating training data makes language models better
Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, and Nicholas Carlini · 2021
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Does bert pretrained on clinical notes reveal sensitive data?, 2021
Eric Lehman, Sarthak Jain, Karl Pichotta, Yoav Goldberg, and Byron C. Wallace · 2021
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Learning with user-level privacy
Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, and Ananda Theertha Suresh · 2021
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Large language models can be strong differentially private learners
Xuechen Li, Florian Tramer, Percy Liang, and Tatsunori Hashimoto · 2021
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Anonymisation models for text data: State of the art, challenges and future directions
Pierre Lison, Ildikó Pilán, David Sánchez, Montserrat Batet, and Lilja Øvrelid · 2021
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Membership inference on word embedding and beyond
Saeed Mahloujifar, Huseyin A Inan, Melissa Chase, Esha Ghosh, and Marcello Hasegawa · 2021
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Adversary instantiation: Lower bounds for differentially private machine learning
Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, and Nicholas Carlini · 2021
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Membership inference attacks against nlp classification models
Virat Shejwalkar, Huseyin A Inan, Amir Houmansadr, and Robert Sim · 2021
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Selective differential privacy for language modeling
Weiyan Shi, Aiqi Cui, Evan Li, Ruoxi Jia, and Zhou Yu · 2021
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Who should apologise: Expressing criticism of public figures on Chinese social media in times of COVID-19
Yingnian Tao · 2021
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Understanding unintended memorization in language models under federated learning
Om Dipakbhai Thakkar, Swaroop Ramaswamy, Rajiv Mathews, and Françoise Beaufays · 2021
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The Social Media Privacy Model: Privacy and Communication in the Light of Social Media Affordances
Sabine Trepte · 2021
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Ethical and social risks of harm from language models, 2021
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, Zac Kenton, Sasha Brown, Will Hawkins, Tom Stepleton, Courtney Biles, Abeba Birhane, Julia Haas, Laura Rimell, Lisa Anne Hendricks, William Isaac, Sean Legassick, Geoffrey Irving, and Iason Gabriel · 2021
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Systems and methods for automatically scrubbing sensitive data, April 29 2021
David Williams · 2021
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Differentially private fine-tuning of language models
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, et al · 2021
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Are larger pretrained language models uniformly better? comparing performance at the instance level
Ruiqi Zhong, Dhruba Ghosh, Dan Klein, and Jacob Steinhardt · 2021
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Suicide hotline shares data with for-profit spinoff, raising ethical questions, Jan 2022
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