IROF: a low resource evaluation metric for explanation methods

9 March 2020

Papers citing "IROF: a low resource evaluation metric for explanation methods"

10 / 10 papers shown

Title
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics Lukas Klein Carsten T. Lüth U. Schlegel Till J. Bungert Mennatallah El-Assady Paul F. Jäger XAI ELM 42 2 0 03 Jan 2025
A Tale of Two Imperatives: Privacy and Explainability Supriya Manna Niladri Sett 94 0 0 30 Dec 2024
Benchmarking the Attribution Quality of Vision Models Robin Hesse Simone Schaub-Meyer Stefan Roth FAtt 34 3 0 16 Jul 2024
A Fresh Look at Sanity Checks for Saliency Maps Anna Hedström Leander Weber Sebastian Lapuschkin Marina M.-C. Höhne FAtt LRM 37 5 0 03 May 2024
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation Xuexin Chen Ruichu Cai Zhengting Huang Yuxuan Zhu Julien Horwood Zhifeng Hao Zijian Li Jose Miguel Hernandez-Lobato AAML 36 2 0 13 Feb 2024
A comprehensive study on fidelity metrics for XAI Miquel Miró-Nicolau Antoni Jaume-i-Capó Gabriel Moyà Alcover 33 11 0 19 Jan 2024
An adversarial attack approach for eXplainable AI evaluation on deepfake detection models Balachandar Gowrisankar V. Thing AAML 28 11 0 08 Dec 2023
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
Evaluating Feature Attribution Methods in the Image Domain Arne Gevaert Axel-Jan Rousseau Thijs Becker D. Valkenborg T. D. Bie Yvan Saeys FAtt 21 22 0 22 Feb 2022
Evaluating and Aggregating Feature-based Model Explanations Umang Bhatt Adrian Weller J. M. F. Moura XAI 30 218 0 01 May 2020