Unsupervised Out-of-Domain Detection via Pre-trained Transformers (2021.acl-long)
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| Challenge: | Prior work on out-of-domain detection requires in-domain task labels and is limited to supervised classification scenarios. |
| Approach: | They propose a method to construct out-of-domain detectors efficiently using pre-trained transformers. |
| Outcome: | The proposed method greatly improves out-of-domain detection ability in a more general scenario. |
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| Challenge: | Existing methods for detecting out-of-domain (OOD) intents are unsupervised and require extensive labeled data. |
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