OpenAutoNLU：面向自然語言理解的開源自動機器學習庫

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 是一款專注於自然語言理解任務的開源自動機器學習函式庫，涵蓋文字分類與命名實體識別兩大功能。有別於現有解決方案，我們創新引入無需人工設定的數據感知訓練機制選擇功能。該函式庫更整合了數據質量診斷、可配置的分布外檢測，以及大型語言模型特性，所有功能皆透過極簡化的低代碼API實現。演示應用程式可於 https://openautonlu.dev 網址存取。

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.