Interpretability is in the eye of the beholder: Human versus artificial
classification of image segments generated by humans versus XAI

v1v2 (latest)

Interpretability is in the eye of the beholder: Human versus artificial classification of image segments generated by humans versus XAI

21 November 2023

ArXiv (abs)PDF HTML

Papers citing "Interpretability is in the eye of the beholder: Human versus artificial classification of image segments generated by humans versus XAI"

17 / 17 papers shown

Title
Post hoc Explanations may be Ineffective for Detecting Unknown Spurious Correlation Julius Adebayo M. Muelly H. Abelson Been Kim 67 87 0 09 Dec 2022
CRAFT: Concept Recursive Activation FacTorization for Explainability Thomas Fel Agustin Picard Louis Bethune Thibaut Boissin David Vigouroux Julien Colin Rémi Cadène Thomas Serre 70 115 0 17 Nov 2022
Perception Visualization: Seeing Through the Eyes of a DNN Loris Giulivi Mark J. Carman Giacomo Boracchi 79 6 0 21 Apr 2022
Human Attention in Fine-grained Classification Yao Rong Wenjia Xu Zeynep Akata Enkelejda Kasneci 88 37 0 02 Nov 2021
Crowdsourcing Evaluation of Saliency-based XAI Methods Xiaotian Lu A. Tolmachev Tatsuya Yamamoto Koh Takeuchi Seiji Okajima T. Takebayashi Koji Maruhashi H. Kashima XAI FAtt 41 14 0 27 Jun 2021
Matching Representations of Explainable Artificial Intelligence and Eye Gaze for Human-Machine Interaction Tiffany Hwu Mia Levy Steven Skorheim David J. Huber 30 6 0 30 Jan 2021
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 111 74 0 18 Jan 2021
How Useful Are the Machine-Generated Interpretations to General Users? A Human Evaluation on Guessing the Incorrectly Predicted Labels Hua Shen Ting-Hao 'Kenneth' Huang FAtt HAI 60 56 0 26 Aug 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 75 161 0 11 Aug 2020
Interpreting Interpretations: Organizing Attribution Methods by Criteria Zifan Wang Piotr (Peter) Mardziel Anupam Datta Matt Fredrikson XAI FAtt 41 17 0 19 Feb 2020
Sanity Checks for Saliency Metrics Richard J. Tomsett Daniel Harborne Supriyo Chakraborty Prudhvi K. Gurram Alun D. Preece XAI 100 170 0 29 Nov 2019
Explaining and Interpreting LSTMs L. Arras Jose A. Arjona-Medina Michael Widrich G. Montavon Michael Gillhofer K. Müller Sepp Hochreiter Wojciech Samek FAtt AI4TS 53 79 0 25 Sep 2019
XRAI: Better Attributions Through Regions A. Kapishnikov Tolga Bolukbasi Fernanda Viégas Michael Terry FAtt XAI 59 212 0 06 Jun 2019
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 188 6,015 0 04 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 321 20,070 0 07 Oct 2016
Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions? Abhishek Das Harsh Agrawal C. L. Zitnick Devi Parikh Dhruv Batra 102 466 0 11 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,027 0 16 Feb 2016