:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Meisenbacher, Stephen, Klymenko, Alexandra, Kelley, Patrick Gage, Peddinti, Sai Teja, Thomas, Kurt, Matthes, Florian
Format:	Preprint
Published:	2024
Subjects:	Computers and Society
Online Access:	https://arxiv.org/abs/2407.02027
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

"We are not Future-ready": Understanding AI Privacy Risks and Existing Mitigation Strategies from the Perspective of AI Developers in Europe
by: Klymenko, Alexandra, et al.
Published: (2025)

LLM-as-a-Judge for Privacy Evaluation? Exploring the Alignment of Human and LLM Perceptions of Privacy in Textual Data
by: Meisenbacher, Stephen, et al.
Published: (2025)

SoK: Privacy Risks and Mitigations in Retrieval-Augmented Generation Systems
by: Bodea, Andreea-Elena, et al.
Published: (2026)

Towards A Structured Overview of Use Cases for Natural Language Processing in the Legal Domain: A German Perspective
by: Vladika, Juraj, et al.
Published: (2024)

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice
by: Maloku, Anxhela, et al.
Published: (2026)

Investigating User Perspectives on Differentially Private Text Privatization
by: Meisenbacher, Stephen, et al.
Published: (2025)

A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking The Privacy-Utility Trade-off
by: Meisenbacher, Stephen, et al.
Published: (2024)

The Double-edged Sword of LLM-based Data Reconstruction: Understanding and Mitigating Contextual Vulnerability in Word-level Differential Privacy Text Sanitization
by: Meisenbacher, Stephen, et al.
Published: (2025)

With Privacy, Size Matters: On the Importance of Dataset Size in Differentially Private Text Rewriting
by: Meisenbacher, Stephen, et al.
Published: (2025)

Thinking Outside of the Differential Privacy Box: A Case Study in Text Privatization with Language Model Prompting
by: Meisenbacher, Stephen, et al.
Published: (2024)

Just Rewrite It Again: A Post-Processing Method for Enhanced Semantic Similarity and Privacy Preservation of Differentially Private Rewritten Text
by: Meisenbacher, Stephen, et al.
Published: (2024)

Leveraging Semantic Triples for Private Document Generation with Local Differential Privacy Guarantees
by: Meisenbacher, Stephen, et al.
Published: (2025)

What Security and Privacy Transparency Users Need from Consumer-Facing Generative AI
by: Cao, Jiaxun, et al.
Published: (2026)

How Generative AI Empowers Attackers and Defenders Across the Trust & Safety Landscape
by: Kelley, Patrick Gage, et al.
Published: (2025)

A Collocation-based Method for Addressing Challenges in Word-level Metric Differential Privacy
by: Meisenbacher, Stephen, et al.
Published: (2024)

1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy
by: Meisenbacher, Stephen, et al.
Published: (2024)

Understanding Help Seeking for Digital Privacy, Safety, and Security
by: Thomas, Kurt, et al.
Published: (2026)

When Explainability Meets Privacy: An Investigation at the Intersection of Post-hoc Explainability and Differential Privacy in the Context of Natural Language Processing
by: Dhaini, Mahdi, et al.
Published: (2025)

Spend Your Budget Wisely: Towards an Intelligent Distribution of the Privacy Budget in Differentially Private Text Rewriting
by: Meisenbacher, Stephen, et al.
Published: (2025)

A Systematic Exploration of Text Decomposition and Budget Distribution in Differentially Private Text Obfuscation
by: Meisenbacher, Stephen, et al.
Published: (2026)

Lexical Substitution is not Synonym Substitution: On the Importance of Producing Contextually Relevant Word Substitutes
by: Vladika, Juraj, et al.
Published: (2025)

On the Impact of Noise in Differentially Private Text Rewriting
by: Meisenbacher, Stephen, et al.
Published: (2025)

SoK: A Framework for Unifying At-Risk User Research
by: Warford, Noel, et al.
Published: (2021)

Frontier AI's Impact on the Cybersecurity Landscape
by: Potter, Yujin, et al.
Published: (2025)

A Case Study on the Impact of Anonymization Along the RAG Pipeline
by: Bodea, Andreea-Elena, et al.
Published: (2026)

A Taxonomy of Systemic Risks from General-Purpose AI
by: Uuk, Risto, et al.
Published: (2024)

AI Risk-Management Standards Profile for General-Purpose AI (GPAI) and Foundation Models
by: Barrett, Anthony M., et al.
Published: (2025)

Effective Mitigations for Systemic Risks from General-Purpose AI
by: Uuk, Risto, et al.
Published: (2024)

An Improved Method for Class-specific Keyword Extraction: A Case Study in the German Business Registry
by: Meisenbacher, Stephen, et al.
Published: (2024)

How Knowledge Workers Think Generative AI Will (Not) Transform Their Industries
by: Woodruff, Allison, et al.
Published: (2023)

DP-MLM: Differentially Private Text Rewriting Using Masked Language Models
by: Meisenbacher, Stephen, et al.
Published: (2024)

Evaluating Privacy Perceptions, Experience, and Behavior of Software Development Teams
by: Prybylo, Maxwell, et al.
Published: (2024)

Extracting O*NET Features from the NLx Corpus to Build Public Use Aggregate Labor Market Data
by: Meisenbacher, Stephen, et al.
Published: (2025)

Automated Generation of Accurate Privacy Captions From Android Source Code Using Large Language Models
by: Jain, Vijayanta, et al.
Published: (2026)

Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
by: Gipiškis, Rokas, et al.
Published: (2024)

Practitioners' Perspectives on a Differential Privacy Deployment Registry
by: Nanayakkara, Priyanka, et al.
Published: (2025)

LLMs for Cyber Security: New Opportunities
by: Divakaran, Dinil Mon, et al.
Published: (2024)

LLM-Powered Analysis of IoT User Reviews: Tracking and Ranking Security and Privacy Concerns
by: Protick, Taufiq Islam, et al.
Published: (2026)

"It didn't feel right but I needed a job so desperately": Understanding People's Emotions & Help Needs During Financial Scams
by: Chanenson, Jake, et al.
Published: (2026)

The Case for ESM3 as a General-Purpose AI Model with Systemic Risk Under the EU AI Act
by: Qureshi, Taro, et al.
Published: (2026)