Papers with Macro F1 score
Subasa - Adapting Language Models for Low-resourced Offensive Language Detection in Sinhala (2025.naacl-srw)
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Shanilka Haturusinghe, Tharindu Cyril Weerasooriya, Christopher M Homan, Marcos Zampieri, Sidath Ravindra Liyanage
| Challenge: | A major challenge in the field of NLP are the disparities between high- and low-resource languages. |
| Approach: | They propose fine-tuning strategies that have not been previously explored for Sinhala in the downstream task of offensive language detection. |
| Outcome: | The proposed models outperform baseline models on the Sinhala offensive language detection task. |
SciNLI: A Corpus for Natural Language Inference on Scientific Text (2022.acl-long)
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| Challenge: | Existing Natural Language Inference (NLI) datasets are not related to scientific text. |
| Approach: | They propose a large dataset for NLI that captures the formality in scientific text and contains 107,412 sentence pairs extracted from scholarly papers on NLP and computational linguistics. |
| Outcome: | The proposed model achieves a Macro F1 score of only 78.18% and an accuracy of 78.23%. |