This post is a brief summary about the paper that I read for my study and curiosity, so I shortly arrange the content of the paper, titled An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction (Larson et al. EMNLP 2019), that I read and studied.

They release new dataset for out-of-scope intent classification.

The dataset is CLINC which can look into CLINC github.

I would summarize what I study on the paper, titled An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction (Larson et al. EMNLP 2019)

Reference

• Paper

  • EMNLP Version: An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction (Larson et al. EMNLP 2019)
  • ArXiv Version: An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction (Larson et al. EMNLP 2019)
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• Inforamtive other paper related to this post

  • ICLR Version: A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks (Hendrycks and Gimpel 2017 ICLR)

  • ArXiv Version: A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks (Hendrycks and Gimpel 2017)

  • ICLR Version: Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks (Liang et al. ICLR 2018)

  • ArXiv Version: Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks (Liang et al. 2018)

  • Korean Version
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