iSee: Advancing Multi-Shot Explainable AI Using Case-based Recommendations

23 August 2024

Papers citing "iSee: Advancing Multi-Shot Explainable AI Using Case-based Recommendations"

7 / 7 papers shown

Title
XEQ Scale for Evaluating XAI Experience Quality A. Wijekoon Nirmalie Wiratunga D. Corsar Kyle Martin Ikechukwu Nkisi-Orji Belén Díaz-Agudo Derek Bridge 174 2 0 20 Jan 2025
This changes to that : Combining causal and non-causal explanations to generate disease progression in capsule endoscopy Anuja Vats A. Mohammed Marius Pedersen Nirmalie Wiratunga MedIm 48 9 0 05 Dec 2022
Behaviour Trees for Creating Conversational Explanation Experiences A. Wijekoon D. Corsar Nirmalie Wiratunga 49 3 0 11 Nov 2022
A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations Barry Smyth Mark T. Keane CML 73 27 0 22 Jan 2021
Captum: A unified and generic model interpretability library for PyTorch Narine Kokhlikyan Vivek Miglani Miguel Martin Edward Wang B. Alsallakh ... Alexander Melnikov Natalia Kliushkina Carlos Araya Siqi Yan Orion Reblitz-Richardson FAtt 144 846 0 16 Sep 2020
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques Vijay Arya Rachel K. E. Bellamy Pin-Yu Chen Amit Dhurandhar Michael Hind ... Karthikeyan Shanmugam Moninder Singh Kush R. Varshney Dennis L. Wei Yunfeng Zhang XAI 67 393 0 06 Sep 2019
Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions Oscar Li Hao Liu Chaofan Chen Cynthia Rudin 178 591 0 13 Oct 2017