mlsanityData to 14 Oct 2026

OpenAutoNLU: Open Source AutoML Library for NLU

arXiv 2603.01824 ↗First posted 2 Mar 2026cs.CL cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 22 references that are in the map. First posted on arXiv 2 Mar 2026.

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17 of 22 references.

References · 17

  1. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,501
  2. 2020Efficient Intent Detection with Dual Sentence Encoderscited by 433
  3. 2020Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamicscited by 425
  4. 2020AutoGluon-Tabular: Robust and Accurate AutoML for Structured Datacited by 383
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  6. 2021Understanding Dataset Difficulty with V-Usable Informationcited by 291
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  8. 2023Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performancecited by 147
  9. 2022MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languagescited by 146
  10. 2022Efficient Few-Shot Learning Without Promptscited by 137
  11. 2021Out-of-Scope Intent Detection with Self-Supervision and Discriminative Trainingcited by 42
  12. 2019Dataset2Vec: Learning Dataset Meta-Featurescited by 38
5 more
  1. 2021LightAutoML: AutoML Solution for a Large Financial Services Ecosystemcited by 32
  2. 2021Learning from Crowds with Crowd-Kitcited by 24
  3. 2025Text Classification in the LLM Era -- Where do we stand?cited by 10
  4. 2023Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Taskscited by 5
  5. 2023A Methodology for Generative Spelling Correction via Natural Spelling Errors Emulation across Multiple Domains and Languagescited by 5

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