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Adversarial TCAV -- Robust and Effective Interpretation of Intermediate
  Layers in Neural Networks
v1v2 (latest)

Adversarial TCAV -- Robust and Effective Interpretation of Intermediate Layers in Neural Networks

10 February 2020
Rahul Soni
Naresh Shah
Chua Tat Seng
J. D. Moore
    AAMLFAtt
ArXiv (abs)PDFHTML

Papers citing "Adversarial TCAV -- Robust and Effective Interpretation of Intermediate Layers in Neural Networks"

7 / 7 papers shown
Probing the Probes: Methods and Metrics for Concept Alignment
Probing the Probes: Methods and Metrics for Concept Alignment
Jacob Lysnæs-Larsen
Marte Eggen
Inga Strümke
LLMSV
226
0
0
06 Nov 2025
On The Variability of Concept Activation Vectors
On The Variability of Concept Activation Vectors
Julia Wenkmann
Damien Garreau
AAML
139
1
0
28 Sep 2025
A survey on Concept-based Approaches For Model Improvement
A survey on Concept-based Approaches For Model Improvement
Avani Gupta
P. J. Narayanan
LRM
353
6
0
21 Mar 2024
Concept Distillation: Leveraging Human-Centered Explanations for Model
  Improvement
Concept Distillation: Leveraging Human-Centered Explanations for Model ImprovementNeural Information Processing Systems (NeurIPS), 2023
Avani Gupta
Saurabh Saini
P. J. Narayanan
272
12
0
26 Nov 2023
Understanding and Enhancing Robustness of Concept-based Models
Understanding and Enhancing Robustness of Concept-based ModelsAAAI Conference on Artificial Intelligence (AAAI), 2022
Sanchit Sinha
Mengdi Huai
Jianhui Sun
Aidong Zhang
AAML
249
28
0
29 Nov 2022
Concept Activation Regions: A Generalized Framework For Concept-Based
  Explanations
Concept Activation Regions: A Generalized Framework For Concept-Based ExplanationsNeural Information Processing Systems (NeurIPS), 2022
Jonathan Crabbé
M. Schaar
335
72
0
22 Sep 2022
Towards interpreting ML-based automated malware detection models: a
  survey
Towards interpreting ML-based automated malware detection models: a survey
Yuzhou Lin
Xiaolin Chang
323
8
0
15 Jan 2021
1
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