Cover Image

InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vinod, Vishnu, Pillutla, Krishna, Thakurta, Abhradeep Guha
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computation and Language Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy
by: Dvijotham, Krishnamurthy, et al.
Published: (2024)

Preserving Expert-Level Privacy in Offline Reinforcement Learning
by: Sharma, Navodita, et al.
Published: (2024)

Correlated Noise Provably Beats Independent Noise for Differentially Private Learning
by: Choquette-Choo, Christopher A., et al.
Published: (2023)

Privacy Amplification for Matrix Mechanisms
by: Choquette-Choo, Christopher A., et al.
Published: (2023)

Fine-Tuning Large Language Models with User-Level Differential Privacy
by: Charles, Zachary, et al.
Published: (2024)

An Inversion Theorem for Buffered Linear Toeplitz (BLT) Matrices and Applications to Streaming Differential Privacy
by: McMahan, H. Brendan, et al.
Published: (2025)

Training Large ASR Encoders with Differential Privacy
by: Chauhan, Geeticka, et al.
Published: (2024)

On Design Principles for Private Adaptive Optimizers
by: Ganesh, Arun, et al.
Published: (2025)

Correlated Noise Mechanisms for Differentially Private Learning
by: Pillutla, Krishna, et al.
Published: (2025)

User Inference Attacks on Large Language Models
by: Kandpal, Nikhil, et al.
Published: (2023)

Optimal Rates for $O(1)$-Smooth DP-SCO with a Single Epoch and Large Batches
by: Choquette-Choo, Christopher A., et al.
Published: (2024)

DP-MGTD: Privacy-Preserving Machine-Generated Text Detection via Adaptive Differentially Private Entity Sanitization
by: Wang, Lionel Z., et al.
Published: (2026)

Privacy-Preserving Transformers: SwiftKey's Differential Privacy Implementation
by: Abouelenin, Abdelrahman, et al.
Published: (2025)

The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
by: Meeus, Matthieu, et al.
Published: (2025)

Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG)
by: Mori, Junki, et al.
Published: (2025)

The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
by: Steinke, Thomas, et al.
Published: (2024)

Differentially Private Knowledge Distillation via Synthetic Text Generation
by: Flemings, James, et al.
Published: (2024)

Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning
by: Chua, Lynn, et al.
Published: (2024)

The Hidden Cost of Modeling P(X): Vulnerability to Membership Inference Attacks in Generative Text Classifiers
by: Makroo, Owais, et al.
Published: (2025)

Private Gradient Descent for Linear Regression: Tighter Error Bounds and Instance-Specific Uncertainty Estimation
by: Brown, Gavin, et al.
Published: (2024)

IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute Randomization
by: Frikha, Ahmed, et al.
Published: (2024)

Privacy-Preserving Data Deduplication for Enhancing Federated Learning of Language Models (Extended Version)
by: Abadi, Aydin, et al.
Published: (2024)

ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities?
by: Liu, Peihan, et al.
Published: (2026)

Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries
by: Huang, Yu-Hsiang, et al.
Published: (2024)

Privacy-Preserving Synthetic Review Generation with Diverse Writing Styles Using LLMs
by: Atwal, Tevin, et al.
Published: (2025)

Personalized Differential Privacy for Ridge Regression
by: Acharya, Krishna, et al.
Published: (2024)

Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints
by: Shejwalkar, Virat, et al.
Published: (2022)

Improving Privacy Benefits of Redaction
by: Gusain, Vaibhav, et al.
Published: (2025)

A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage
by: Xin, Rui, et al.
Published: (2025)

Optimizing the Privacy-Utility Balance using Synthetic Data and Configurable Perturbation Pipelines
by: Sharma, Anantha, et al.
Published: (2025)

Policy-Invisible Violations in LLM-Based Agents
by: Wu, Jie, et al.
Published: (2026)

Membership Inference Attacks and Privacy in Topic Modeling
by: Manzonelli, Nico, et al.
Published: (2024)

Two Birds with One Stone: Multi-Task Detection and Attribution of LLM-Generated Text
by: Rao, Zixin, et al.
Published: (2025)

Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks
by: Zhang, Xinyu, et al.
Published: (2023)

Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack
by: Zhou, Ying, et al.
Published: (2024)

FreqMark: Frequency-Based Watermark for Sentence-Level Detection of LLM-Generated Text
by: Xu, Zhenyu, et al.
Published: (2024)

What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation?
by: Buchholz, Erik, et al.
Published: (2025)

IDT: Dual-Task Adversarial Attacks for Privacy Protection
by: Faustini, Pedro, et al.
Published: (2024)

Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation
by: Li, Xianzhi, et al.
Published: (2024)

Privacy Preserving In-Context-Learning Framework for Large Language Models
by: Bhusal, Bishnu, et al.
Published: (2025)