Taxonomy Of Xai Methods Download Scientific Diagram A living and curated collection of explainable ai methods interactively browse and contribute to a curated categorization of papers on explainable ai. the initial dataset was collected and labelled by nauta et al. (2023) as part of a large scale literature review on the evaluation of explainable artificial intelligence. This survey also contributes to the call for objective, quantifiable evaluation methods by presenting an extensive overview of quantitative xai evaluation methods. our systematic collection of evaluation methods provides researchers and practitioners with concrete tools to thoroughly validate, benchmark and compare new and existing xai methods.
Taxonomy Of Xai Methods Download Scientific Diagram A thorough investigation concerning the quantitative evaluation of xai methods was proposed by the work of nauta et al. [12], identifying 12 conceptual aspects, introduced as co 12 properties, that serve as a categorization scheme for reviewing the evaluation practice. The high level categories in existing taxonomies for xai evaluation. doshi velez and kim (2018), hoffman et al. (2018, 2023), and lopes et al. (2022) discuss both evaluation with users (green) and without users (orange); nauta et al. (2023) focus on evaluation without users (orange); zhou et al. (2021), vilone and longo (2021), and mohseni et al. (2021) focus on evaluation with users (green. This survey also contributes to the call for objective, quantiiable evaluation methods by presenting an extensive overview of quantitative xai evaluation methods. our systematic collection of evaluation methods provides researchers and practitioners with concrete tools to thoroughly validate, benchmark and compare new and existing xai methods. Overview of xai methods (nauta et al.) utwente dmb.github.io 26 2 comments elisa nguyen reposted this michael kirchhof apple machine learning research intern working on uncertainty quantification.
Overview Of The Reported Xai Methods Download Scientific Diagram This survey also contributes to the call for objective, quantiiable evaluation methods by presenting an extensive overview of quantitative xai evaluation methods. our systematic collection of evaluation methods provides researchers and practitioners with concrete tools to thoroughly validate, benchmark and compare new and existing xai methods. Overview of xai methods (nauta et al.) utwente dmb.github.io 26 2 comments elisa nguyen reposted this michael kirchhof apple machine learning research intern working on uncertainty quantification. In the most recent literature review, nauta et al. [19] highlighted that 33% of the research was evaluated using anecdotal evidence, 58% applied quantitative evaluation, 22% evaluated human subjects in a user study, and 23% of the research was evaluated using domain experts, i.e., application grounded evaluation. We adopt the categorization by [nauta et al., 2023], who define 12 desirable criteria (co 12) for functionally grounded evaluation and present a comprehensive list of data types and explanation types. in contrast to previous xai eval uation surveys, we focus on xai evaluation toolkits from a practical perspective.
2 Taxonomy Of Xai Methods Download Scientific Diagram In the most recent literature review, nauta et al. [19] highlighted that 33% of the research was evaluated using anecdotal evidence, 58% applied quantitative evaluation, 22% evaluated human subjects in a user study, and 23% of the research was evaluated using domain experts, i.e., application grounded evaluation. We adopt the categorization by [nauta et al., 2023], who define 12 desirable criteria (co 12) for functionally grounded evaluation and present a comprehensive list of data types and explanation types. in contrast to previous xai eval uation surveys, we focus on xai evaluation toolkits from a practical perspective.