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False Claims against Model Ownership Resolution
v1v2v3v4v5v6v7 (latest)

False Claims against Model Ownership Resolution

13 April 2023
Jian Liu
Rui Zhang
S. Szyller
Kui Ren
Nirmal Asokan
    AAMLMLAU
ArXiv (abs)PDFHTML

Papers citing "False Claims against Model Ownership Resolution"

27 / 27 papers shown
Title
ImF: Implicit Fingerprint for Large Language Models
ImF: Implicit Fingerprint for Large Language Models
Wu jiaxuan
Peng Wanli
Fu hang
Xue Yiming
Wen juan
148
0
0
25 Mar 2025
FIT-Print: Towards False-claim-resistant Model Ownership Verification via Targeted Fingerprint
FIT-Print: Towards False-claim-resistant Model Ownership Verification via Targeted Fingerprint
Shuo Shao
Haozhe Zhu
Hongwei Yao
Yiming Li
Tianwei Zhang
Zhan Qin
Kui Ren
AAML
463
0
0
26 Jan 2025
GENIE: Watermarking Graph Neural Networks for Link Prediction
GENIE: Watermarking Graph Neural Networks for Link Prediction
Venkata Sai Pranav Bachina
Ankit Gangwal
Aaryan Ajay Sharma
Charu Sharma
129
2
0
07 Jun 2024
MetaV: A Meta-Verifier Approach to Task-Agnostic Model Fingerprinting
MetaV: A Meta-Verifier Approach to Task-Agnostic Model Fingerprinting
Xudong Pan
Yifan Yan
Mi Zhang
Min Yang
80
24
0
19 Jan 2022
A survey of deep neural network watermarking techniques
A survey of deep neural network watermarking techniques
Yue Li
Hongxia Wang
Mauro Barni
119
147
0
16 Mar 2021
Proof-of-Learning: Definitions and Practice
Proof-of-Learning: Definitions and Practice
Hengrui Jia
Mohammad Yaghini
Christopher A. Choquette-Choo
Natalie Dullerud
Anvith Thudi
Varun Chandrasekaran
Nicolas Papernot
AAML
76
106
0
09 Mar 2021
A Systematic Review on Model Watermarking for Neural Networks
A Systematic Review on Model Watermarking for Neural Networks
Franziska Boenisch
AAML
68
69
0
25 Sep 2020
Imitation Attacks and Defenses for Black-box Machine Translation Systems
Imitation Attacks and Defenses for Black-box Machine Translation Systems
Eric Wallace
Mitchell Stern
Basel Alomair
AAML
98
123
0
30 Apr 2020
Cryptanalytic Extraction of Neural Network Models
Cryptanalytic Extraction of Neural Network Models
Nicholas Carlini
Matthew Jagielski
Ilya Mironov
FedMLMLAUMIACVAAML
138
137
0
10 Mar 2020
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas
Yuxuan Zhang
Florian Kerschbaum
MLAUFedMLAAML
101
146
0
02 Dec 2019
Thieves on Sesame Street! Model Extraction of BERT-based APIs
Thieves on Sesame Street! Model Extraction of BERT-based APIs
Kalpesh Krishna
Gaurav Singh Tomar
Ankur P. Parikh
Nicolas Papernot
Mohit Iyyer
MIACVMLAU
131
201
0
27 Oct 2019
Similarity of Neural Network Representations Revisited
Similarity of Neural Network Representations Revisited
Simon Kornblith
Mohammad Norouzi
Honglak Lee
Geoffrey E. Hinton
145
1,436
0
01 May 2019
Adversarial Training for Free!
Adversarial Training for Free!
Ali Shafahi
Mahyar Najibi
Amin Ghiasi
Zheng Xu
John P. Dickerson
Christoph Studer
L. Davis
Gavin Taylor
Tom Goldstein
AAML
139
1,253
0
29 Apr 2019
How to Prove Your Model Belongs to You: A Blind-Watermark based
  Framework to Protect Intellectual Property of DNN
How to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN
Zheng Li
Chengyu Hu
Yang Zhang
Shanqing Guo
AAML
57
173
0
05 Mar 2019
Towards Federated Learning at Scale: System Design
Towards Federated Learning at Scale: System Design
Keith Bonawitz
Hubert Eichner
W. Grieskamp
Dzmitry Huba
A. Ingerman
...
H. B. McMahan
Timon Van Overveldt
David Petrou
Daniel Ramage
Jason Roselander
FedML
128
2,676
0
04 Feb 2019
Improving Transferability of Adversarial Examples with Input Diversity
Improving Transferability of Adversarial Examples with Input Diversity
Cihang Xie
Zhishuai Zhang
Yuyin Zhou
Song Bai
Jianyu Wang
Zhou Ren
Alan Yuille
AAML
113
1,127
0
19 Mar 2018
Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks
  by Backdooring
Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring
Yossi Adi
Carsten Baum
Moustapha Cissé
Benny Pinkas
Joseph Keshet
68
682
0
13 Feb 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILMOOD
319
12,151
0
19 Jun 2017
Enhancing Robustness of Machine Learning Systems via Data
  Transformations
Enhancing Robustness of Machine Learning Systems via Data Transformations
A. Bhagoji
Daniel Cullina
Chawin Sitawarin
Prateek Mittal
AAML
80
231
0
09 Apr 2017
Embedding Watermarks into Deep Neural Networks
Embedding Watermarks into Deep Neural Networks
Yusuke Uchida
Yuki Nagai
S. Sakazawa
Shiníchi Satoh
122
611
0
15 Jan 2017
Delving into Transferable Adversarial Examples and Black-box Attacks
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
Basel Alomair
AAML
145
1,741
0
08 Nov 2016
Stealing Machine Learning Models via Prediction APIs
Stealing Machine Learning Models via Prediction APIs
Florian Tramèr
Fan Zhang
Ari Juels
Michael K. Reiter
Thomas Ristenpart
SILMMLAU
109
1,813
0
09 Sep 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
549
5,912
0
08 Jul 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
362
8,005
0
23 May 2016
Practical Black-Box Attacks against Machine Learning
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAUAAML
85
3,685
0
08 Feb 2016
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,145
0
20 Dec 2014
Deep Learning Face Attributes in the Wild
Deep Learning Face Attributes in the Wild
Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
268
8,433
0
28 Nov 2014
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