XAIT: An interactive website for explainable ai for text
Erick Oduor, Kun Qian, et al.
IUI 2020
A comprehensive benchmark is crucial for evaluating automated Business Intelligence (BI) systems and their real-world effectiveness. We propose a holistic, end-to-end framework that assesses BI systems based on the quality, relevance, and depth of insights. It categorizes queries into descriptive, diagnostic, predictive, and prescriptive types, aligning with practical BI needs. Our fully automated approach enables custom benchmark generation tailored to specific datasets. Additionally, we introduce an automated evaluation mechanism that removes reliance on strict ground truth, ensuring scalable and adaptable assessments. By addressing key limitations, our user-centered framework offers a flexible and robust methodology for advancing next-generation BI systems.
Erick Oduor, Kun Qian, et al.
IUI 2020
Kenya Andrews, Lamogha Chiazor
AAAI 2025
Mehant Kammakomati, Sameer Pimparkhede, et al.
ACL 2025
Subhajit Chaudhury, Sarathkrishna Swaminathan, et al.
ACL 2023