On a Utilitarian Approach to Privacy Preserving Text Generation

On a Utilitarian Approach to Privacy Preserving Text Generation

23 April 2021

Abhinav Aggarwal

Oluwaseyi Feyisetan

Nathanael Teissier

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Papers citing "On a Utilitarian Approach to Privacy Preserving Text Generation"

16 / 16 papers shown

Title
Synopsis: Secure and private trend inference from encrypted semantic embeddings Madelyne Xiao Palak Jain Micha Gorelick Sarah Scheffler 423 0 0 29 May 2025
Inspecting the Representation Manifold of Differentially-Private Text Stefan Arnold 212 1 0 19 Mar 2025
Investigating User Perspectives on Differentially Private Text Privatization Stephen Meisenbacher Alexandra Klymenko Alexander Karpp Florian Matthes 173 1 0 12 Mar 2025
Private Language Models via Truncated Laplacian MechanismConference on Empirical Methods in Natural Language Processing (EMNLP), 2024 Tianhao Huang Tao Yang Ivan Habernal Lijie Hu Di Wang 169 2 0 10 Oct 2024
A Collocation-based Method for Addressing Challenges in Word-level Metric Differential Privacy Stephen Meisenbacher Maulik Chevli Florian Matthes 209 3 0 30 Jun 2024
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs Charlie Hou Akshat Shrivastava Hongyuan Zhan Rylan Conway Trang Le Adithya Sagar Giulia Fanti Daniel Lazar 232 25 0 05 Jun 2024
Just Rewrite It Again: A Post-Processing Method for Enhanced Semantic Similarity and Privacy Preservation of Differentially Private Rewritten Text Stephen Meisenbacher Florian Matthes 166 8 0 30 May 2024
Words Blending Boxes. Obfuscating Queries in Information Retrieval using Differential Privacy Francesco Luigi De Faveri G. Faggioli Nicola Ferro AAML 128 1 0 15 May 2024
$1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy$ 1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy Stephen Meisenbacher Maulik Chevli Florian Matthes 154 11 0 02 May 2024
A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking The Privacy-Utility Trade-offInternational Conference on Language Resources and Evaluation (LREC), 2024 Stephen Meisenbacher Nihildev Nandakumar Alexandra Klymenko Florian Matthes 158 14 0 04 Apr 2024
Guiding Text-to-Text Privatization by Syntax Stefan Arnold Dilara Yesilbas Sven Weinzierl 145 15 0 02 Jun 2023
Driving Context into Text-to-Text Privatization Stefan Arnold Dilara Yesilbas Sven Weinzierl 170 10 0 02 Jun 2023
Differentially Private Natural Language Models: Recent Advances and Future DirectionsFindings (Findings), 2023 Lijie Hu Ivan Habernal Lei Shen Haiyan Zhao AAML 180 23 0 22 Jan 2023
Swing Distillation: A Privacy-Preserving Knowledge Distillation Framework Junzhuo Li Xinwei Wu Weilong Dong Shuangzhi Wu Chao Bian Deyi Xiong 260 5 0 16 Dec 2022
Synthetic Text Generation with Differential Privacy: A Simple and Practical RecipeAnnual Meeting of the Association for Computational Linguistics (ACL), 2022 Xiang Yue Huseyin A. Inan Xuechen Li Girish Kumar Julia McAnallen Hoda Shajari Huan Sun David Levitan Robert Sim 254 111 0 25 Oct 2022
The Limits of Word Level Differential Privacy Justus Mattern Benjamin Weggenmann Florian Kerschbaum 164 62 0 02 May 2022