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Found 5 papers, 2 papers with code
I-CEE: Tailoring Explanations of Image Classification Models to User Expertise
Informed by existing work, I-CEE explains the decisions of image classification models by providing the user with an informative subset of training data (i. e., example images), corresponding local explanations, and model decisions.
GO-DICE: Goal-Conditioned Option-Aware Offline Imitation Learning via Stationary Distribution Correction Estimation
Offline imitation learning (IL) refers to learning expert behavior solely from demonstrations, without any additional interaction with the environment.
Automated Task-Time Interventions to Improve Teamwork using Imitation Learning
To improve teamwork in these and other domains, we present TIC: an automated intervention approach for improving coordination between team members.
Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations
A better understanding of the needs of XAI users, as well as human-centered evaluations of explainable models are both a necessity and a challenge.
Explainable Artificial Intelligence (XAI)
Explainable Models
+2
A Bayesian Approach to Identifying Representational Errors
Trained AI systems and expert decision makers can make errors that are often difficult to identify and understand.
