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VISION DIFFMASK: Faithful Interpretation of Vision Transformers with
  Differentiable Patch Masking

VISION DIFFMASK: Faithful Interpretation of Vision Transformers with Differentiable Patch Masking

13 April 2023
A. Nalmpantis
Apostolos Panagiotopoulos
John Gkountouras
Konstantinos Papakostas
Wilker Aziz
ArXiv (abs)PDFHTMLGithub (29★)

Papers citing "VISION DIFFMASK: Faithful Interpretation of Vision Transformers with Differentiable Patch Masking"

5 / 5 papers shown
Inherently Faithful Attention Maps for Vision Transformers
Inherently Faithful Attention Maps for Vision Transformers
Ananthu Aniraj
C. Dantas
Dino Ienco
Diego Marcos
OODOCL
519
1
0
10 Jun 2025
LVLM-Interpret: An Interpretability Tool for Large Vision-Language
  Models
LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models
Gabriela Ben-Melech Stan
Estelle Aflalo
R. Y. Rohekar
Anahita Bhiwandiwalla
Shao-Yen Tseng
Matthew Lyle Olson
Yaniv Gurwicz
Chenfei Wu
Nan Duan
Vasudev Lal
442
14
0
03 Apr 2024
Adventures of Trustworthy Vision-Language Models: A Survey
Adventures of Trustworthy Vision-Language Models: A Survey
Mayank Vatsa
Anubhooti Jain
Richa Singh
251
10
0
07 Dec 2023
Explainability of Vision Transformers: A Comprehensive Review and New
  Perspectives
Explainability of Vision Transformers: A Comprehensive Review and New Perspectives
Rojina Kashefi
Leili Barekatain
Mohammad Sabokrou
Fatemeh Aghaeipoor
ViT
280
19
0
12 Nov 2023
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
2.5K
19,701
0
16 Feb 2016
1