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How Useful are Gradients for OOD Detection Really?

How Useful are Gradients for OOD Detection Really?

20 May 2022
Conor Igoe
Youngseog Chung
I. Char
J. Schneider
    OODD
ArXiv (abs)PDFHTMLGithub

Papers citing "How Useful are Gradients for OOD Detection Really?"

16 / 16 papers shown
Probabilistic Runtime Verification, Evaluation and Risk Assessment of Visual Deep Learning Systems
Probabilistic Runtime Verification, Evaluation and Risk Assessment of Visual Deep Learning Systems
Birk Torpmann-Hagen
Pål Halvorsen
Michael A. Riegler
Dag Johansen
164
0
0
23 Sep 2025
An Empirical Analysis of VLM-based OOD Detection: Mechanisms, Advantages, and Sensitivity
An Empirical Analysis of VLM-based OOD Detection: Mechanisms, Advantages, and Sensitivity
YuXiao Lee
Xiaofeng Cao
Wei Ye
Jiangchao Yao
Jingkuan Song
Heng Tao Shen
MLLM
269
0
0
16 Sep 2025
Concept Matching with Agent for Out-of-Distribution Detection
Concept Matching with Agent for Out-of-Distribution Detection
YuXiao Lee
Xiaofeng Cao
Jingcai Guo
Wei Ye
Qing Guo
Yi Chang
376
0
0
08 Jan 2025
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future DirectionsACM Computing Surveys (ACM CSUR), 2024
Ola Shorinwa
Zhiting Mei
Justin Lidard
Allen Z. Ren
Anirudha Majumdar
HILMLRM
527
19
0
07 Dec 2024
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
Pursuing Feature Separation based on Neural Collapse for Out-of-Distribution Detection
Yingwen Wu
Ruiji Yu
Xinwen Cheng
Zhengbao He
Xiaolin Huang
OODD
448
9
0
28 May 2024
Epistemic Uncertainty Quantification For Pre-trained Neural Network
Epistemic Uncertainty Quantification For Pre-trained Neural Network
Hanjing Wang
Qiang Ji
UQCV
220
11
0
15 Apr 2024
Approximations to the Fisher Information Metric of Deep Generative
  Models for Out-Of-Distribution Detection
Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection
Sam Dauncey
Chris Holmes
Christopher Williams
Fabian Falck
405
2
0
03 Mar 2024
GROOD: GRadient-Aware Out-of-Distribution Detection
GROOD: GRadient-Aware Out-of-Distribution Detection
Mostafa ElAraby
Sabyasachi Sahoo
Y. Pequignot
Paul Novello
Liam Paull
353
0
0
22 Dec 2023
GAIA: Delving into Gradient-based Attribution Abnormality for
  Out-of-distribution Detection
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
Jinggang Chen
Junjie Li
Xiaoyang Qu
Jianzong Wang
Jiguang Wan
Jing Xiao
OODD
300
13
0
16 Nov 2023
Out-of-distribution Detection Learning with Unreliable
  Out-of-distribution Sources
Out-of-distribution Detection Learning with Unreliable Out-of-distribution SourcesNeural Information Processing Systems (NeurIPS), 2023
Haotian Zheng
Qizhou Wang
Zhen Fang
Xiaobo Xia
Yifan Zhang
Tongliang Liu
Bo Han
532
45
0
06 Nov 2023
Learning to Augment Distributions for Out-of-Distribution Detection
Learning to Augment Distributions for Out-of-Distribution DetectionNeural Information Processing Systems (NeurIPS), 2023
Qizhou Wang
Zhen Fang
Yonggang Zhang
Yifan Zhang
Shouqing Yang
Bo Han
OODD
530
55
0
03 Nov 2023
Low-Dimensional Gradient Helps Out-of-Distribution Detection
Low-Dimensional Gradient Helps Out-of-Distribution DetectionIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Yingwen Wu
Tao Li
Xinwen Cheng
Jie Yang
Xiaolin Huang
OODD
250
9
0
26 Oct 2023
Meta OOD Learning for Continuously Adaptive OOD Detection
Meta OOD Learning for Continuously Adaptive OOD DetectionIEEE International Conference on Computer Vision (ICCV), 2023
Xinheng Wu
Jie Lu
Zhen Fang
Guangquan Zhang
OODD
329
15
0
21 Sep 2023
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with
  Orthogonal Projection of Gradients
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of GradientsNeural Information Processing Systems (NeurIPS), 2023
Sima Behpour
T. Doan
Xin Li
Wenbin He
Liangke Gou
Liu Ren
OODD
349
27
0
01 Aug 2023
T2FNorm: Extremely Simple Scaled Train-time Feature Normalization for
  OOD Detection
T2FNorm: Extremely Simple Scaled Train-time Feature Normalization for OOD Detection
Sudarshan Regmi
Bibek Panthi
S. Dotel
P. Gyawali
Danail Stoynov
Binod Bhattarai
OODD
213
5
0
28 May 2023
Generalized Out-of-Distribution Detection: A Survey
Generalized Out-of-Distribution Detection: A SurveyInternational Journal of Computer Vision (IJCV), 2021
Jingkang Yang
Kaiyang Zhou
Shouqing Yang
Ziwei Liu
939
1,329
0
21 Oct 2021
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