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2311.17035
Cited By
Scalable Extraction of Training Data from (Production) Language Models
28 November 2023
Milad Nasr
Nicholas Carlini
Jonathan Hayase
Matthew Jagielski
A. Feder Cooper
Daphne Ippolito
Christopher A. Choquette-Choo
Eric Wallace
Florian Tramèr
Katherine Lee
SILM
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HuggingFace (3 upvotes)
Papers citing
"Scalable Extraction of Training Data from (Production) Language Models"
50 / 281 papers shown
Analyzing Memorization in Large Language Models through the Lens of Model Attribution
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Xiangkui Cao
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254
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Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning
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Kai Y. Xiao
Johannes Heidecke
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AAML
183
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24 Dec 2024
Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models
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Elisa Nguyen
Michael Simeone
Erik Johnston
Martin Gubri
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20 Dec 2024
Jailbreaking? One Step Is Enough!
Annual Meeting of the Association for Computational Linguistics (ACL), 2024
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Peijian Zeng
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Hongyan Wu
Hongyan Wu
Jianfei Chen
Aimin Yang
Yimiao Zhou
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224
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17 Dec 2024
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Christopher A. Choquette-Choo
Miranda Bogen
Matthew Jagielski
Katja Filippova
...
Hanna M. Wallach
Amy Cyphert
Katherine Lee
Nicolas Papernot
Katherine Lee
MU
AILaw
357
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0
09 Dec 2024
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Duncan McClements
Madhavendra Thakur
454
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Learning to Forget using Hypernetworks
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Stefan Schoepf
Jack Foster
David M. Krueger
Usman Anwar
MU
367
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AIDBench: A benchmark for evaluating the authorship identification capability of large language models
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Dadi Guo
Huishuai Zhang
268
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Measuring Non-Adversarial Reproduction of Training Data in Large Language Models
International Conference on Learning Representations (ICLR), 2024
Michael Aerni
Javier Rando
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243
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167
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Yash More
Jackie CK Cheung
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573
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Radhika Bhargava
Kyle Hinsz
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257
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S´ebastien Marcel
289
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Exactly Minimax-Optimal Locally Differentially Private Sampling
Neural Information Processing Systems (NeurIPS), 2024
Hyun-Young Park
Shahab Asoodeh
Si-Hyeon Lee
288
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Props for Machine-Learning Security
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Farinaz Koushanfar
150
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C. Park
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KELM
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164
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Shuchao Pang
Zhigang Lu
Jian Shu
Peng Fu
Yongbin Zhou
Minhui Xue
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431
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16 Oct 2024
To Err is AI : A Case Study Informing LLM Flaw Reporting Practices
AAAI Conference on Artificial Intelligence (AAAI), 2024
Sean McGregor
Allyson Ettinger
Nick Judd
Paul Albee
Liwei Jiang
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Avijit Ghosh
Christopher Fiorelli
Michelle Hoang
Sven Cattell
Nouha Dziri
200
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A Theoretical Survey on Foundation Models
Shi Fu
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Yingjie Wang
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304
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Federated Learning in Practice: Reflections and Projections
International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (ICPSISA), 2024
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Hubert Eichner
Peter Kairouz
H. B. McMahan
Daniel Ramage
Zheng Xu
FedML
317
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COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act
Philipp Guldimann
Alexander Spiridonov
Robin Staab
Nikola Jovanović
Mark Vero
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Mislav Balunović
Nikola Konstantinov
Pavol Bielik
Petar Tsankov
Martin Vechev
ELM
353
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Rescriber: Smaller-LLM-Powered User-Led Data Minimization for LLM-Based Chatbots
International Conference on Human Factors in Computing Systems (CHI), 2024
Jijie Zhou
Eryue Xu
Yaoyao Wu
Tianshi Li
411
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CodeCipher: Learning to Obfuscate Source Code Against LLMs
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Chengcheng Wan
Yixiong Fang
Xiaodong Gu
155
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KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Server
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Wenhao Wang
Xiaoyu Liang
Rui Ye
Jingyi Chai
Siheng Chen
Yanfeng Wang
SyDa
338
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Kemal Derya
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AAML
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How Much Can We Forget about Data Contamination?
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Suraj Srinivas
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451
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Aswathy Ajith
Arham Khan
Nathaniel Hudson
Caleb Geniesse
Kyle Chard
Yaoqing Yang
Ian Foster
Michael W. Mahoney
KELM
MU
396
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Suzan Verberne
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Shengyuan Hu
Neil Kale
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Virginia Smith
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357
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Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data
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Debeshee Das
Gautam Kamath
Florian Tramèr
MIALM
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826
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Predicting memorization within Large Language Models fine-tuned for classification
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Davide Buscaldi
A. Shabou
Sonia Vanier
340
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An Adversarial Perspective on Machine Unlearning for AI Safety
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Boyi Wei
Yangsibo Huang
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MU
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935
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Data-Centric AI Governance: Addressing the Limitations of Model-Focused Policies
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Leah Walker
Rodolfo Corona
Stephanie Fu
Suzanne Petryk
Janet Napolitano
Trevor Darrell
Andrew W. Reddie
ELM
212
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Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Weichao Zhang
Ruqing Zhang
Jiafeng Guo
Maarten de Rijke
Yixing Fan
Xueqi Cheng
439
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Order of Magnitude Speedups for LLM Membership Inference
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Rongting Zhang
Martín Bertrán
Aaron Roth
443
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Unlocking Memorization in Large Language Models with Dynamic Soft Prompting
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Zhepeng Wang
Runxue Bao
Yawen Wu
Jackson Taylor
Cao Xiao
Feng Zheng
Weiwen Jiang
Shangqian Gao
Yanfu Zhang
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205
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Extracting Memorized Training Data via Decomposition
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Anu Vellore
Amy Chang
Raffaele Mura
Blaine Nelson
Paul Kassianik
Amin Karbasi
193
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MEOW: MEMOry Supervised LLM Unlearning Via Inverted Facts
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Kexin Huang
Ruilin Luo
Yuanqi Yao
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Yingchun Wang
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359
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Junjie Chu
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Giada Pistilli
Kritika Maheshwari
Riccardo Fusaroli
47
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Huan Yee Koh
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Lauren T. May
Geoffrey I. Webb
Shirui Pan
George Church
LM&MA
241
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Yishi Xu
Zhewei Huang
Shuchang Zhou
Jianbin Jiao
Junge Zhang
PILM
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345
8
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Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage
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Md Rafi Ur Rashid
Jing Liu
T. Koike-Akino
Shagufta Mehnaz
Ye Wang
MU
SILM
327
11
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Yijia Shao
Tianshi Li
Weiyan Shi
Yanchen Liu
Diyi Yang
PILM
550
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Junyuan Hong
Chulin Xie
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Rachel Xin
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Zinan Lin
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Bingsheng He
Dawn Song
ELM
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311
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Samuel Greiff
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Dragan Gašević
446
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225
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