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Seeing the Forest through the Trees: Data Leakage from Partial
  Transformer Gradients

Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients

3 June 2024
Weijun Li
Qiongkai Xu
Mark Dras
    PILM
ArXivPDFHTML

Papers citing "Seeing the Forest through the Trees: Data Leakage from Partial Transformer Gradients"

4 / 4 papers shown
Title
Empirical Calibration and Metric Differential Privacy in Language Models
Empirical Calibration and Metric Differential Privacy in Language Models
Pedro Faustini
Natasha Fernandes
Annabelle McIver
Mark Dras
65
0
0
18 Mar 2025
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning
  for Language Models
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
Liam H. Fowl
Jonas Geiping
Steven Reich
Yuxin Wen
Wojtek Czaja
Micah Goldblum
Tom Goldstein
FedML
73
56
0
29 Jan 2022
Opacus: User-Friendly Differential Privacy Library in PyTorch
Opacus: User-Friendly Differential Privacy Library in PyTorch
Ashkan Yousefpour
I. Shilov
Alexandre Sablayrolles
Davide Testuggine
Karthik Prasad
...
Sayan Gosh
Akash Bharadwaj
Jessica Zhao
Graham Cormode
Ilya Mironov
VLM
168
350
0
25 Sep 2021
Gradient-based Adversarial Attacks against Text Transformers
Gradient-based Adversarial Attacks against Text Transformers
Chuan Guo
Alexandre Sablayrolles
Hervé Jégou
Douwe Kiela
SILM
106
227
0
15 Apr 2021
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