Web: http://arxiv.org/abs/2209.06612

Sept. 15, 2022, 1:14 a.m. | Yanan Wu, Zhiyuan Zeng, Keqing He, Yutao Mou, Pei Wang, Weiran Xu

cs.CL updates on arXiv.org arxiv.org

Out-of-Domain (OOD) detection is a key component in a task-oriented dialog
system, which aims to identify whether a query falls outside the predefined
supported intent set. Previous softmax-based detection algorithms are proved to
be overconfident for OOD samples. In this paper, we analyze overconfident OOD
comes from distribution uncertainty due to the mismatch between the training
and test distributions, which makes the model can't confidently make
predictions thus probably causing abnormal softmax scores. We propose a
Bayesian OOD detection framework …

approximation arxiv bayesian detection distribution

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