Papers by Jes Frellsen
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity (2022.findings-emnlp)
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| Challenge: | Using low-resource languages, we assess the quality of uncertainty estimates from a wide array of approaches, but with more data. |
| Approach: | They train models on sub-sampled datasets in three different languages to assess the confidence of a neural classifier. |
| Outcome: | The proposed models train on sub-sampled datasets in three different languages and show that the quality of uncertainty estimates suffers with more data. |