Papers with token-level F1-score
Negation typology and general representation models for cross-lingual zero-shot negation scope resolution in Russian, French, and Spanish. (2021.naacl-srw)
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| Challenge: | Negation resolution remains an acute and continuously researched question in Natural Language Processing. |
| Approach: | They propose to use multilingual pre-trained general representation models to detect negation scope in languages without annotated data. |
| Outcome: | The proposed model achieves token-level F1 score between English, Spanish, French, and Russian. |