CLSep 25, 2025

AutoIntent: AutoML for Text Classification

arXiv:2509.21138v12 citationsh-index: 1EMNLP
Originality Incremental advance
AI Analysis

This tool addresses the need for efficient and automated text classification for users in natural language processing, though it appears incremental as it builds on existing AutoML solutions.

AutoIntent is an automated machine learning tool for text classification that tackles the problem of automating model selection, optimization, and tuning, resulting in superior performance on standard datasets while balancing effectiveness and resource consumption.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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