Papers by Joanna Baran
Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks (2023.acl-srw)
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| Challenge: | Current approaches to OOD detection in NLP are not yet sufficiently sensitive to capture all samples characterized by various types of distributional shifts. |
| Approach: | They evaluated eight methods that are easily integrable into existing NLP systems and require no additional OOD data or model modifications. |
| Outcome: | The proposed methods are easily integrable into existing NLP systems and require no additional OOD data or model modifications. |