Unsupervised Out-of-Domain Detection via Pre-trained Transformers. (arXiv:2106.00948v2 [cs.CL] UPDATED)

Deployed real-world machine learning applications are often subject to
uncontrolled and even potentially malicious inputs. Those out-of-domain inputs
can lead to unpredictable outputs and sometimes catastrophic safety issues.
Prior studies on out-of-domain detection require in-domain task labels and are
limited to supervised classification scenarios. Our work tackles the problem of
detecting out-of-domain samples with only unsupervised in-domain data. We
utilize the latent representations of pre-trained transformers and propose a
simple yet effective method to transform features across all layers to …

arxiv detection transformers unsupervised