Vicinal Risk Minimization for Few-Shot Cross-lingual Transfer in Abusive Language Detection (2023.emnlp-main)
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| Challenge: | Existing methods for few-shot cross-lingual transfer learning are limited in target languages due to the scarcity of resources. |
| Approach: | They propose a method which interpolates pairs of instances based on the angle of their representations and propose augmentation methods to enhance few-shot cross-lingual abusive language detection. |
| Outcome: | The proposed method improves few-shot cross-lingual abusive language detection in seven languages typologically distinct from English and three different domains. |
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| Challenge: | a lack of labeled data for low-resource languages leads to the need for effective cross-lingual transfer learning. |
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