Out-of-scope intent detection with intent-invariant data augmentation

Fanshu Sun, Heyan Huang, Puhai Yang, Heng-Da Xu, Xianling Mao

Abstract: Highlights•Enhance Out-Of-Scope (OOS) intent detection with intent-invariant data augmentation.•Our method effectively reduces the two kinds of low-quality augmentations.•Our method balances the validity and the diversity of the augmented OOS data.•Extensive experiments show that our method outperforms state-of-the-art baselines.