Crowdsourcing Evaluation of Saliency-based XAI Methods

Crowdsourcing Evaluation of Saliency-based XAI Methods

27 June 2021

Tatsuya Yamamoto

Papers citing "Crowdsourcing Evaluation of Saliency-based XAI Methods"

10 / 10 papers shown

Title
A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning Eura Nofshin Esther Brown Brian Lim Weiwei Pan Finale Doshi-Velez 42 0 0 31 May 2024
Evaluating Saliency Explanations in NLP by Crowdsourcing Xiaotian Lu Jiyi Li Zhen Wan Xiaofeng Lin Koh Takeuchi Hisashi Kashima XAI FAtt LRM 27 1 0 17 May 2024
Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image Classification Matteo Bianchi Antonio De Santis Andrea Tocchetti Marco Brambilla MILM FAtt 32 1 0 06 May 2024
How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps Romy Müller HAI 45 6 0 03 Apr 2024
Interpretability is in the eye of the beholder: Human versus artificial classification of image segments generated by humans versus XAI Romy Müller Marius Thoss Julian Ullrich Steffen Seitz Carsten Knoll 24 3 0 21 Nov 2023
Multiview Representation Learning from Crowdsourced Triplet Comparisons Xiaotian Lu Jiyi Li Koh Takeuchi H. Kashima SSL 17 2 0 08 Feb 2023
Trustworthy Human Computation: A Survey H. Kashima S. Oyama Hiromi Arai Junichiro Mori 27 0 0 22 Oct 2022
When and How to Fool Explainable Models (and Humans) with Adversarial Examples Jon Vadillo Roberto Santana Jose A. Lozano SILM AAML 36 12 0 05 Jul 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 48 170 0 13 Jan 2021
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,690 0 28 Feb 2017