Generating Counterfactual and Contrastive Explanations using SHAP

21 June 2019

Papers citing "Generating Counterfactual and Contrastive Explanations using SHAP"

17 / 17 papers shown

Title
Rectifying Group Irregularities in Explanations for Distribution Shift Adam Stein Yinjun Wu Eric Wong Mayur Naik 37 1 0 25 May 2023
CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions Julia El Zini Mohamad Mansour M. Awad 33 1 0 19 Jan 2023
MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation Wenzhuo Yang Jia Li Caiming Xiong Guosheng Lin CML 35 13 0 31 May 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 38 78 0 06 May 2022
Interpretation of Black Box NLP Models: A Survey Shivani Choudhary N. Chatterjee S. K. Saha FAtt 34 10 0 31 Mar 2022
Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning Sindre Benjamin Remman Inga Strümke A. Lekkas CML 15 7 0 04 Nov 2021
Counterfactual Shapley Additive Explanations Emanuele Albini Jason Long Danial Dervovic Daniele Magazzeni 26 49 0 27 Oct 2021
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey Richard Dazeley Peter Vamplew Francisco Cruz 32 59 0 20 Aug 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data Raphael Mazzine David Martens 40 33 0 09 Jul 2021
Evaluating the Correctness of Explainable AI Algorithms for Classification Orcun Yalcin Xiuyi Fan Siyuan Liu XAI FAtt 16 15 0 20 May 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 47 176 0 07 Mar 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 44 95 0 02 Mar 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
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 26 162 0 20 Oct 2020
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses Kaivalya Rawal Himabindu Lakkaraju 27 11 0 15 Sep 2020
SCOUT: Self-aware Discriminant Counterfactual Explanations Pei Wang Nuno Vasconcelos FAtt 30 81 0 16 Apr 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 27 213 0 09 Mar 2020