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Natural language processing models have experienced a significant upsurge in recent years, with numerous applications being built upon them.
Membership inference attacks from first principles. In 2022 IEEE Symposium on Security and Privacy (SP) . IEEE, 1897–1914
Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, and Florian Tramer. 2022a · 1914
Earlier work this paper cites.
Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee. 2005 · 1914
Earlier work this paper cites.
Membership inference attacks against NLP classification models. In NeurIPS 2021 Workshop Privacy in Machine Learning . 1897–1914
Virat Shejwalkar, Huseyin A Inan, Amir Houmansadr, and Robert Sim. 2021 · 1914
Earlier work this paper cites.
SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter. In Proceedings of the 13th International Workshop on Semantic Evaluation . Association for Computational Linguistics, Minneapolis, Minnesota, USA, 54–63
Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza, Viviana Patti, Francisco Manuel Rangel Pardo, Paolo Rosso, and Manuela Sanguinetti. 2019 · 2007
Earlier work this paper cites.
The algorithmic foundations of differential privacy
Cynthia Dwork, Aaron Roth, et al · 2014
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014 · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
Earlier work this paper cites.
Deep learning with differential privacy. In Proceedings of the 2016 ACM SIGSAC conference on computer and communications security . 308–318
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang. 2016 · 2016
Earlier work this paper cites.
An overview of gradient descent optimization algorithms
Sebastian Ruder. 2016 · 2016
Earlier work this paper cites.
Membership inference attacks against machine learning models. In 2017 IEEE symposium on security and privacy (SP) . IEEE, 3–18
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov. 2017 · 2017
Earlier work this paper cites.
SoK: Security and privacy in machine learning. In 2018 IEEE European Symposium on Security and Privacy (EuroS&P) . IEEE, 399–414
Nicolas Papernot, Patrick McDaniel, Arunesh Sinha, and Michael P Wellman. 2018 · 2018
Earlier work this paper cites.
Towards demystifying membership inference attacks
Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei. 2018 · 2018
Earlier work this paper cites.
Memguard: Defending against black-box membership inference attacks via adversarial examples. In Proceedings of the 2019 ACM SIGSAC conference on computer and communications security . 259–274
Jinyuan Jia, Ahmed Salem, Michael Backes, Yang Zhang, and Neil Zhenqiang Gong. 2019 · 2019
Earlier work this paper cites.
SocInf: Membership inference attacks on social media health data with machine learning
Gaoyang Liu, Chen Wang, Kai Peng, Haojun Huang, Yutong Li, and Wenqing Cheng. 2019b · 2019
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. 2019a · 2019
Earlier work this paper cites.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Cited alongside, same era.
Auditing Data Provenance in Text-Generation Models. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Anchorage, AK, USA) (KDD ’19) . Association for Computing Machinery, New York, NY, USA, 196–206
Congzheng Song and Vitaly Shmatikov. 2019 · 2019
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020 · 2020
Cited alongside, same era.
A Survey of Privacy Attacks in Machine Learning
Maria Rigaki and Sebastian Garcia. 2020 · 2020
Cited alongside, same era.
Against membership inference attack: Pruning is all you need
Scaling Instruction-Finetuned Language Models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei. 2022 · 2022
Later among the works it cites.
An efficient DP-SGD mechanism for large scale NLU models. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 4118–4122
Christophe Dupuy, Radhika Arava, Rahul Gupta, and Anna Rumshisky. 2022 · 2022
Later among the works it cites.
Submix: Practical private prediction for large-scale language models
Antonio Ginart, Laurens van der Maaten, James Zou, and Chuan Guo. 2022 · 2022
Later among the works it cites.
Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models
Xinlei He, Zheng Li, Weilin Xu, Cory Cornelius, and Yang Zhang. 2022 · 2022
Later among the works it cites.
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Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, and Sanguthevar Rajasekaran. 2020 · 2020
Cited alongside, same era.
Transformers: State-of-the-Art Natural Language Processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations . Association for Computational Linguistics, Online, 38–45
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi 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 M. Rush. 2020 · 2020
Cited alongside, same era.
Extracting training data from large language models. In 30th USENIX Security Symposium (USENIX Security 21) . 2633–2650
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
Cited alongside, same era.
DP-FP: Differentially Private Forward Propagation for Large Models
Jian Du and Haitao Mi. 2021 · 2021
Cited alongside, same era.
LoRA: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
Membership inference attack susceptibility of clinical language models
Abhyuday Jagannatha, Bhanu Pratap Singh Rawat, and Hong Yu. 2021 · 2021
Cited alongside, same era.
When does data augmentation help with membership inference attacks?. In International conference on machine learning . PMLR, 5345–5355
Yigitcan Kaya and Tudor Dumitras. 2021 · 2021
Cited alongside, same era.
Security and privacy in machine learning: A survey
Gayatri Sravanthi Kuntla, Xin Tian, and Zhigang Li. 2021 · 2021
Cited alongside, same era.
Membership inference attacks on machine learning: A survey
Hongsheng Hu, Zoran Salcic, Lichao Sun, Gillian Dobbie, Philip S Yu, and Xuyun Zhang. 2022 · 2022
Later among the works it cites.
Differentially private decoding in large language models
Jimit Majmudar, Christophe Dupuy, Charith Peris, Sami Smaili, Rahul Gupta, and Richard Zemel. 2022 · 2022
Later among the works it cites.
Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. In 2022 IEEE International Conference on Big Data (Big Data) . IEEE, 5823–5832
Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, and Sanguthevar Rajasekaran. 2022 · 2022
Later among the works it cites.
SoK: Membership Inference is Harder Than Previously Thought
Antreas Dionysiou and Elias Athanasopoulos. 2023 · 2023
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Defenses to Membership Inference Attacks: A Survey
Li Hu, Anli Yan, Hongyang Yan, Jin Li, Teng Huang, Yingying Zhang, Changyu Dong, and Chunsheng Yang. 2023 · 2023
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Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models
Matthieu Meeus, Shubham Jain, Marek Rei, and Yves-Alexandre de Montjoye. 2023 · 2023
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Recent advances in natural language processing via large pre-trained language models: A survey
Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heintz, and Dan Roth. 2023 · 2023
Later among the works it cites.
SoK: Comparing Different Membership Inference Attacks with a Comprehensive Benchmark
Jun Niu, Xiaoyan Zhu, Moxuan Zeng, Ge Zhang, Qingyang Zhao, Chunhui Huang, Yangming Zhang, Suyu An, Yangzhong Wang, Xinghui Yue, et al · 2023
Later among the works it cites.
Improved Membership Inference Attacks Against Language Classification Models. In arXiv:2310.07219
Shlomit Shachor, Natalia Razinkov, and Abigail Goldsteen. 2023 · 2023
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Bag of tricks for training data extraction from language models
Weichen Yu, Tianyu Pang, Qian Liu, Chao Du, Bingyi Kang, Yan Huang, Min Lin, and Shuicheng Yan. 2023 · 2023
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Demystifying membership inference attacks in machine learning as a service
Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei. 2019 · 2089
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