@inproceedings{
melamed2023explaining,
title={Explaining high-dimensional text classifiers},
author={Odelia Melamed and Rich Caruana},
booktitle={XAI in Action: Past, Present, and Future Applications},
year={2023},
url={https://openreview.net/forum?id=wNhcShUyAf}
}
Explainability has become a valuable tool in the last few years, helping humans better understand AI-guided decisions. However, the classic explainability tools are sometimes quite limited when considering high-dimensional inputs and neural network classifiers. We present a new explainability method using theoretically proven high-dimensional properties in neural network classifiers. We present two usages of it: 1) On the classical sentiment analysis task for the IMDB reviews dataset, and 2) our Malware-Detection task for our PowerShell scripts dataset.
Explaining high-dimensional text classifiers
Odelia Melamed Rich Caruana