Abstract
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.
Abstract (translated)
AutoIntent 是一种用于文本分类任务的自动化机器学习工具。与现有的解决方案不同，AutoIntent 提供了端到端的自动化功能，包括嵌入模型选择、分类器优化和决策阈值调整，并且在模块化界面中操作，类似于 sklearn 接口。该框架设计支持多标签分类和未定义范围检测。在标准意图分类数据集上，AutoIntent 的表现优于现有的 AutoML 工具，并使用户能够平衡效率与资源消耗。
URL
https://arxiv.org/abs/2509.21138
