no code implementations • 25 Apr 2024 • Sangwon Seo, Vaibhav Unhelkar
When faced with accomplishing a task, human experts exhibit intentional behavior.
1 code implementation • 19 Dec 2023 • Yao Rong, Peizhu Qian, Vaibhav Unhelkar, Enkelejda Kasneci
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.
no code implementations • 17 Dec 2023 • Abhinav Jain, Vaibhav Unhelkar
Offline imitation learning (IL) refers to learning expert behavior solely from demonstrations, without any additional interaction with the environment.
no code implementations • 1 Mar 2023 • Sangwon Seo, Bing Han, Vaibhav Unhelkar
To improve teamwork in these and other domains, we present TIC: an automated intervention approach for improving coordination between team members.
1 code implementation • 20 Oct 2022 • Yao Rong, Tobias Leemann, Thai-trang Nguyen, Lisa Fiedler, Peizhu Qian, Vaibhav Unhelkar, Tina Seidel, Gjergji Kasneci, Enkelejda Kasneci
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
no code implementations • 28 Mar 2021 • Ramya Ramakrishnan, Vaibhav Unhelkar, Ece Kamar, Julie Shah
Trained AI systems and expert decision makers can make errors that are often difficult to identify and understand.