The Privacy Onion Effect: Memorization is Relative

21 June 2022

Papers citing "The Privacy Onion Effect: Memorization is Relative"

20 / 20 papers shown

Title
Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models C. L. P. Chen Daochang Liu M. Shah Chang Xu 62 1 0 25 Apr 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text Matthieu Meeus Lukas Wutschitz Santiago Zanella Béguelin Shruti Tople Reza Shokri 77 0 0 24 Feb 2025
Captured by Captions: On Memorization and its Mitigation in CLIP Models Wenhao Wang Adam Dziedzic Grace C. Kim Michael Backes Franziska Boenisch 86 0 0 11 Feb 2025
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations Kaixuan Huang Jiacheng Guo Zihao Li X. Ji Jiawei Ge ... Yangsibo Huang Chi Jin Xinyun Chen Chiyuan Zhang Mengdi Wang AAML LRM 95 7 0 10 Feb 2025
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models Vinith M. Suriyakumar Rohan Alur Ayush Sekhari Manish Raghavan Ashia C. Wilson 53 2 0 10 Oct 2024
Position: LLM Unlearning Benchmarks are Weak Measures of Progress Pratiksha Thaker Shengyuan Hu Neil Kale Yash Maurya Zhiwei Steven Wu Virginia Smith MU 53 10 0 03 Oct 2024
AI Data Readiness Inspector (AIDRIN) for Quantitative Assessment of Data Readiness for AI Kaveen Hiniduma Suren Byna J. L. Bez Ravi Madduri 43 5 0 27 Jun 2024
Machine Unlearning Fails to Remove Data Poisoning Attacks Martin Pawelczyk Jimmy Z. Di Yiwei Lu Gautam Kamath Ayush Sekhari Seth Neel AAML MU 57 8 0 25 Jun 2024
Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon USVSN Sai Prashanth Alvin Deng Kyle O'Brien Jyothir S V Mohammad Aflah Khan ... Jacob Ray Fuehne Stella Biderman Tracy Ke Katherine Lee Naomi Saphra 55 12 0 25 Jun 2024
Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models Jingyang Zhang Jingwei Sun Eric C. Yeats Ouyang Yang Martin Kuo Jianyi Zhang Hao Frank Yang Hai Li 43 41 0 03 Apr 2024
FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models Ziqiang Yuan Kaiyuan Wang Shoutai Zhu Ye Yuan Jingya Zhou Yanlin Zhu Wenqi Wei 34 5 0 19 Jan 2024
Fundamental Limits of Membership Inference Attacks on Machine Learning Models Eric Aubinais Elisabeth Gassiat Pablo Piantanida MIACV 48 2 0 20 Oct 2023
What can we learn from Data Leakage and Unlearning for Law? Jaydeep Borkar PILM MU 30 10 0 19 Jul 2023
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD Anvith Thudi Hengrui Jia Casey Meehan Ilia Shumailov Nicolas Papernot 20 3 0 01 Jul 2023
Collaborative Learning via Prediction Consensus Dongyang Fan Celestine Mendler-Dünner Martin Jaggi FedML 29 7 0 29 May 2023
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation Noel Loo Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus DD 26 5 0 02 Feb 2023
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning Vasisht Duddu S. Szyller Nadarajah Asokan 24 12 0 04 Dec 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 281 1,812 0 14 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? Gavin Brown Mark Bun Vitaly Feldman Adam D. Smith Kunal Talwar 245 80 0 11 Dec 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 102 130 0 07 Feb 2020