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Language Models as a Service (LMaaS) offers convenient access for developers and researchers to perform inference using pre-trained language models.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Augmenting data with mixup for sentence classification: An empirical study
Hongyu Guo, Yongyi Mao, and Richong Zhang. 2019 · 1905
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Automatically constructing a corpus of sentential paraphrases
William B. Dolan and Chris Brockett. 2005 · 2005
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Cryptogru: Low latency privacy-preserving text analysis with gru
Bo Feng, Qian Lou, Lei Jiang, and Geoffrey C Fox. 2020 · 2010
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Loose tweets: an analysis of privacy leaks on twitter
Huina Mao, Xin Shuai, and Apu Kapadia. 2011 · 2011
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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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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Security and privacy issues in cloud computing
Jaydip Sen. 2015 · 2015
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Ensuring security and privacy preservation for cloud data services
Jun Tang, Yong Cui, Qi Li, Kui Ren, Jiangchuan Liu, and Rajkumar Buyya. 2016 · 2016
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Privacy-preserving neural representations of text
Maximin Coavoux, Shashi Narayan, and Shay B. Cohen. 2018 · 2018
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Towards robust and privacy-preserving text representations
Yitong Li, Timothy Baldwin, and Trevor Cohn. 2018 · 2018
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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 Bowman. 2018 · 2018
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz. 2018 · 2018
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Heuristic authorship obfuscation
Janek Bevendorff, Martin Potthast, Matthias Hagen, and Benno Stein. 2019 · 2019
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Information leakage in embedding models
Congzheng Song and Ananth Raghunathan. 2020 · 2020
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A differentially private text perturbation method using regularized mahalanobis metric
Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, and Nathanael Teissier. 2020 · 2020
Membership inference attacks against nlp classification models
Virat Shejwalkar, Huseyin A Inan, Amir Houmansadr, and Robert Sim. 2021 · 2021
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Differential privacy for text analytics via natural text sanitization
Xiang Yue, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun, and Sherman S. M. Chow. 2021 · 2021
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A multifaceted framework to evaluate evasion, content preservation, and misattribution in authorship obfuscation techniques
Malik Altakrori, Thomas Scialom, Benjamin C. M. Fung, and Jackie Chi Kit Cheung. 2022 · 2022
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THE-X: Privacy-preserving transformer inference with homomorphic encryption
Tianyu Chen, Hangbo Bao, Shaohan Huang, Li Dong, Binxing Jiao, Daxin Jiang, Haoyi Zhou, Jianxin Li, and Furu Wei. 2022 · 2022
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Label-only model inversion attacks via boundary repulsion
Mostafa Kahla, Si Chen, Hoang Anh Just, and Ruoxi Jia. 2022 · 2022
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Cited alongside, same era.
Learning and evaluating a differentially private pre-trained language model
Shlomo Hoory, Amir Feder, Avichai Tendler, Sofia Erell, Alon Peled-Cohen, Itay Laish, Hootan Nakhost, Uri Stemmer, Ayelet Benjamini, Avinatan Hassidim, and Yossi Matias. 2021 · 2021
Cited alongside, same era.
Co-mixup: Saliency guided joint mixup with supermodular diversity
JangHyun Kim, Wonho Choo, Hosan Jeong, and Hyun Oh Song. 2021 · 2021
Cited alongside, same era.
CAPE: Context-aware private embeddings for private language learning
Richard Plant, Dimitra Gkatzia, and Valerio Giuffrida. 2021 · 2021
Cited alongside, same era.
Natural language understanding with privacy-preserving bert
Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky, and Marc Najork. 2021 · 2021
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A girl has no name: Automated authorship obfuscation using mutant-x
Asad Mahmood, Faizan Ahmad, Zubair Shafiq, Padmini Srinivasan, and Fareed Zaffar. 2022 · 2022
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Black-box tuning for language-model-as-a-service
Tianxiang Sun, Yunfan Shao, Hong Qian, Xuanjing Huang, and Xipeng Qiu. 2022 · 2022
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TextFusion: Privacy-preserving pre-trained model inference via token fusion
Xin Zhou, Jinzhu Lu, Tao Gui, Ruotian Ma, Zichu Fei, Yuran Wang, Yong Ding, Yibo Cheung, Qi Zhang, and Xuanjing Huang. 2022 · 2022
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Sanitizing sentence embeddings (and labels) for local differential privacy
Minxin Du, Xiang Yue, Sherman SM Chow, and Huan Sun. 2023 · 2023
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Offsite-tuning: Transfer learning without full model
Guangxuan Xiao, Ji Lin, and Song Han. 2023 · 2023
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