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1802.08232
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The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks
22 February 2018
Nicholas Carlini
Chang-rui Liu
Ulfar Erlingsson
Jernej Kos
Basel Alomair
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Papers citing
"The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks"
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Locally Differentially Private Embedding Models in Distributed Fraud Prevention Systems
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Piotr Skalski
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181
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IEEE Transactions on Software Engineering (TSE), 2024
Jie Zhu
Leye Wang
Xiao Han
Anmin Liu
Tao Xie
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206
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02 Jan 2024
Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning
ACM Transactions on Management Information Systems (ACM TMIS), 2023
Xiao-Yang Liu
Rongyi Zhu
Daochen Zha
Jiechao Gao
Shan Zhong
Matt White
Yijia Zhao
279
48
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29 Dec 2023
Knowledge Distillation of LLM for Automatic Scoring of Science Education Assessments
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Luyang Fang
Ping Ma
Xiaoming Zhai
254
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DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction)
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Frederick Shpilevskiy
Mathias Lécuyer
208
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Social Learning: Towards Collaborative Learning with Large Language Models
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Florian Hartmann
Sian Gooding
Lukás Zilka
Matt Sharifi
Blaise Agüera y Arcas
247
14
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18 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks
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S. Szyller
Nadarajah Asokan
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380
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07 Dec 2023
Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection
Tuan Hoang
Santu Rana
Sunil R. Gupta
Svetha Venkatesh
BDL
MU
247
35
0
07 Dec 2023
Diffence: Fencing Membership Privacy With Diffusion Models
Yuefeng Peng
Ali Naseh
Amir Houmansadr
AAML
328
4
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07 Dec 2023
Understanding (Un)Intended Memorization in Text-to-Image Generative Models
Ali Naseh
Jaechul Roh
Amir Houmansadr
DiffM
176
6
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06 Dec 2023
Memory Triggers: Unveiling Memorization in Text-To-Image Generative Models through Word-Level Duplication
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Jaechul Roh
Amir Houmansadr
193
7
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06 Dec 2023
Low-Cost High-Power Membership Inference Attacks
International Conference on Machine Learning (ICML), 2023
Sajjad Zarifzadeh
Philippe Liu
Reza Shokri
349
76
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06 Dec 2023
Privacy Measurement in Tabular Synthetic Data: State of the Art and Future Research Directions
Alexander Boudewijn
Andrea Filippo Ferraris
D. Panfilo
Vanessa Cocca
Sabrina Zinutti
Karel De Schepper
Carlo Rossi Chauvenet
175
8
0
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Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective
Lukas Wutschitz
Boris Köpf
Andrew Paverd
Saravan Rajmohan
Ahmed Salem
Shruti Tople
Santiago Zanella Béguelin
Menglin Xia
Victor Rühle
205
17
0
27 Nov 2023
DPSUR: Accelerating Differentially Private Stochastic Gradient Descent Using Selective Update and Release
Proceedings of the VLDB Endowment (PVLDB), 2023
Jie Fu
Qingqing Ye
Haibo Hu
Zhili Chen
Lulu Wang
Kuncan Wang
Xun Ran
285
25
0
23 Nov 2023
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates
International Conference on Algorithmic Learning Theory (ALT), 2023
Michael Menart
Enayat Ullah
Raman Arora
Raef Bassily
Cristóbal Guzmán
304
2
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22 Nov 2023
SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning
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Bowen Li Jie Li
Chentao Wu
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157
6
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22 Nov 2023
Trustworthy Large Models in Vision: A Survey
Ziyan Guo
Kepeng Xu
Jun Liu
MU
656
0
0
16 Nov 2023
Privacy Threats in Stable Diffusion Models
Thomas Cilloni
Charles Fleming
Charles Walter
199
5
0
15 Nov 2023
Towards Verifiable Text Generation with Symbolic References
Lucas Torroba Hennigen
Zejiang Shen
Aniruddha Nrusimha
Bernhard Gapp
David Sontag
Yoon Kim
333
23
0
15 Nov 2023
Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks
North American Chapter of the Association for Computational Linguistics (NAACL), 2023
Ting-Yun Chang
Jesse Thomason
Robin Jia
323
26
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15 Nov 2023
CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation
Annual Meeting of the Association for Computational Linguistics (ACL), 2023
Weixiang Yan
Haitian Liu
Yunkun Wang
Yunzhe Li
Qian Chen
...
Tingyu Lin
Weishan Zhao
Li Zhu
Hari Sundaram
Shuiguang Deng
ELM
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424
52
0
14 Nov 2023
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent
Lauren Watson
Eric Gan
Mohan Dantam
Baharan Mirzasoleiman
Rik Sarkar
189
1
0
12 Nov 2023
Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation
Verna Dankers
Ivan Titov
Dieuwke Hupkes
253
5
0
09 Nov 2023
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State
Koyena Pal
Jiuding Sun
Andrew Yuan
Byron C. Wallace
David Bau
203
90
0
08 Nov 2023
Federated Experiment Design under Distributed Differential Privacy
Wei-Ning Chen
Graham Cormode
Akash Bharadwaj
Peter Romov
Ayfer Özgür
FedML
228
4
0
07 Nov 2023
PrivLM-Bench: A Multi-level Privacy Evaluation Benchmark for Language Models
Annual Meeting of the Association for Computational Linguistics (ACL), 2023
Haoran Li
Dadi Guo
Donghao Li
Wei Fan
Qi Hu
Xin Liu
Chunkit Chan
Duanyi Yao
Yuan Yao
Yangqiu Song
PILM
441
33
0
07 Nov 2023
SoK: Memorisation in machine learning
Dmitrii Usynin
Moritz Knolle
Georgios Kaissis
325
1
0
06 Nov 2023
DP-DCAN: Differentially Private Deep Contrastive Autoencoder Network for Single-cell Clustering
International Conference on Intelligent Computing (ICIC), 2023
Huifa Li
Jie Fu
Zhili Chen
Xiaomin Yang
Haitao Liu
Xinpeng Ling
300
1
0
06 Nov 2023
Advances in Embodied Navigation Using Large Language Models: A Survey
Jinzhou Lin
Han Gao
Xuxiang Feng
Rongtao Xu
Changwei Wang
Man Zhang
Li Guo
Shibiao Xu
LM&Ro
LLMAG
759
21
0
01 Nov 2023
DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Xinwei Wu
Junzhuo Li
Minghui Xu
Weilong Dong
Shuangzhi Wu
Chao Bian
Deyi Xiong
MU
KELM
370
83
0
31 Oct 2023
Where have you been? A Study of Privacy Risk for Point-of-Interest Recommendation
Knowledge Discovery and Data Mining (KDD), 2023
Kunlin Cai
Jinghuai Zhang
Zhiqing Hong
Will Shand
Guang Wang
Desheng Zhang
Jianfeng Chi
Yuan Tian
326
6
0
28 Oct 2023
Proving Test Set Contamination in Black Box Language Models
International Conference on Learning Representations (ICLR), 2023
Yonatan Oren
Nicole Meister
Niladri Chatterji
Faisal Ladhak
Tatsunori B. Hashimoto
HILM
366
198
0
26 Oct 2023
Privately Aligning Language Models with Reinforcement Learning
International Conference on Learning Representations (ICLR), 2023
Fan Wu
Huseyin A. Inan
A. Backurs
Varun Chandrasekaran
Janardhan Kulkarni
Robert Sim
318
11
0
25 Oct 2023
Locally Differentially Private Document Generation Using Zero Shot Prompting
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Saiteja Utpala
Sara Hooker
Pin-Yu Chen
274
59
0
24 Oct 2023
SoK: Memorization in General-Purpose Large Language Models
Valentin Hartmann
Anshuman Suri
Vincent Bindschaedler
David Evans
Shruti Tople
Robert West
KELM
LLMAG
327
37
0
24 Oct 2023
Gradient-Free Privacy Leakage in Federated Language Models through Selective Weight Tampering
Md Rafi Ur Rashid
Vishnu Asutosh Dasu
Kang Gu
Najrin Sultana
Shagufta Mehnaz
AAML
FedML
519
14
0
24 Oct 2023
Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models
USENIX Security Symposium (USENIX Security), 2023
Matthieu Meeus
Shubham Jain
Marek Rei
Yves-Alexandre de Montjoye
MIALM
389
60
0
23 Oct 2023
Fundamental Limits of Membership Inference Attacks on Machine Learning Models
Eric Aubinais
Elisabeth Gassiat
Pablo Piantanida
MIACV
519
4
0
20 Oct 2023
Unintended Memorization in Large ASR Models, and How to Mitigate It
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
Lun Wang
Om Thakkar
Rajiv Mathews
239
8
0
18 Oct 2023
Disentangling the Linguistic Competence of Privacy-Preserving BERT
BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP), 2023
Stefan Arnold
Nils Kemmerzell
Annika Schreiner
252
0
0
17 Oct 2023
Data Contamination Through the Lens of Time
Manley Roberts
Himanshu Thakur
Christine Herlihy
Colin White
Samuel Dooley
302
37
0
16 Oct 2023
Impact of Co-occurrence on Factual Knowledge of Large Language Models
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Cheongwoong Kang
Jaesik Choi
KELM
226
25
0
12 Oct 2023
Beyond Memorization: Violating Privacy Via Inference with Large Language Models
International Conference on Learning Representations (ICLR), 2023
Robin Staab
Mark Vero
Mislav Balunović
Martin Vechev
PILM
324
161
0
11 Oct 2023
No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML
Ziqi Zhang
Chen Gong
Yifeng Cai
Yuanyuan Yuan
Bingyan Liu
Ding Li
Yao Guo
Xiangqun Chen
FedML
189
46
0
11 Oct 2023
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning
International Conference on Learning Representations (ICLR), 2023
Christopher A. Choquette-Choo
Krishnamurthy Dvijotham
Krishna Pillutla
Arun Ganesh
Thomas Steinke
Abhradeep Thakurta
279
20
0
10 Oct 2023
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning
Neural Information Processing Systems (NeurIPS), 2023
Zhiqin Yang
Yonggang Zhang
Yuxiang Zheng
Xinmei Tian
Hao Peng
Tongliang Liu
Bo Han
FedML
196
115
0
08 Oct 2023
PrIeD-KIE: Towards Privacy Preserved Document Key Information Extraction
S. Saifullah
S. Agne
Andreas Dengel
Sheraz Ahmed
180
1
0
05 Oct 2023
Can Language Models be Instructed to Protect Personal Information?
Yang Chen
Ethan Mendes
Sauvik Das
Wei Xu
Alan Ritter
PILM
198
47
0
03 Oct 2023
Source Inference Attacks: Beyond Membership Inference Attacks in Federated Learning
IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2023
Hongsheng Hu
Xuyun Zhang
Z. Salcic
Lichao Sun
K. Choo
Gillian Dobbie
181
28
0
30 Sep 2023
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