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PrivBench: A Holistic and Modular Benchmarking Platform for Evaluating Text-to-Text Privatization

Paper recorded by Signals 4 on 2026-08-30 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.CL · 自然语言处理 · first seen 2026-09-01

Abstract

Natural Language Processing methods have enabled novel solutions and advances in the field of privacy, particularly in the sub-domain of text-to-text privatization, where the goal is to transform a sensitive input text into a privatized output by ideally masking (in)directly identifiable or otherwise private information. The evaluation of text-to-text privatization, however, is not straightforward

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#161 most recent of 186 cs.CL papers we have recorded · ↑ newer: When Does Predictor-Based RL Align with Human Perception? A Study of S · ↓ older: JPO: Juris Policy Optimization for Structured Legal Reasoning in Crimi
Cite this page: PrivBench: A Holistic and Modular Benchmarking Platform for Evaluating Text-to-Text Privatization: the #161 most recent of 186 cs.CL papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/privbench-a-holistic-and-modular-benchmarking-platform-for-evaluating-text-to-te.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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