AutoIntent is an automated machine learning tool for text classification tasks. Unlike existing solutions, AutoIntent offers end-to-end automation with embedding model selection, classifier optimization, and decision threshold tuning, all within a modular, sklearn-like interface. The framework is designed to support multi-label classification and out-of-scope detection. AutoIntent demonstrates superior performance compared to existing AutoML tools on standard intent classification datasets and enables users to balance effectiveness and resource consumption.
@article{arxiv.2509.21138,
title = {AutoIntent: AutoML for Text Classification},
author = {Ilya Alekseev and Roman Solomatin and Darina Rustamova and Denis Kuznetsov},
journal= {arXiv preprint arXiv:2509.21138},
year = {2026}
}