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Identifying Untrustworthy Predictions in Neural Networks by Geometric
  Gradient Analysis

Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis

24 February 2021
Leo Schwinn
A. Nguyen
René Raab
Leon Bungert
Daniel Tenbrinck
Dario Zanca
Martin Burger
Bjoern M. Eskofier
    AAML
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Papers citing "Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis"

2 / 2 papers shown
Title
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space
Leo Schwinn
David Dobre
Sophie Xhonneux
Gauthier Gidel
Stephan Gunnemann
AAML
47
36
0
14 Feb 2024
Robust Out-of-distribution Detection for Neural Networks
Robust Out-of-distribution Detection for Neural Networks
Jiefeng Chen
Yixuan Li
Xi Wu
Yingyu Liang
S. Jha
OODD
150
83
0
21 Mar 2020
1