Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer
Inputs of Language Models in Federated Learning

Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning

10 December 2023

Sheng Liu

Papers citing "Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning"

4 / 4 papers shown

Title
DAGER: Exact Gradient Inversion for Large Language Models Ivo Petrov Dimitar I. Dimitrov Maximilian Baader Mark Niklas Muller Martin Vechev FedML 55 3 0 24 May 2024
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 71 56 0 29 Jan 2022
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 69 181 0 06 Dec 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,956 0 20 Apr 2018