OpenAutoNLU：面向自然语言理解的开源自动机器学习库

OpenAutoNLU: Open Source AutoML Library for NLU

March 2, 2026

作者: Grigory Arshinov, Aleksandr Boriskin, Sergey Senichev, Ayaz Zaripov, Daria Galimzianova, Daniil Karpov, Leonid Sanochkin

cs.AI

摘要

OpenAutoNLU是一款面向自然语言理解任务的开源自动机器学习库，涵盖文本分类与命名实体识别两大功能。与现有方案不同，我们引入了无需用户手动配置的数据感知型训练机制选择技术。该库还提供集成化数据质量诊断、可配置的分布外检测功能以及大语言模型特性，所有功能均通过极简的低代码API实现。演示应用可通过 https://openautonlu.dev 访问。

English

OpenAutoNLU is an open-source automated machine learning library for natural language understanding (NLU) tasks, covering both text classification and named entity recognition (NER). Unlike existing solutions, we introduce data-aware training regime selection that requires no manual configuration from the user. The library also provides integrated data quality diagnostics, configurable out-of-distribution (OOD) detection, and large language model (LLM) features, all within a minimal lowcode API. The demo app is accessible here https://openautonlu.dev.