From Random to Informed Data Selection: A Diversity-Based Approach to Optimize Human Annotation and Few-Shot Learning
Alexandre Alcoforado, Lucas Hideki Takeuchi Okamura, Israel Campos Fama, Bárbara Fernandes Dias Bueno, Arnold Moya Lavado, Thomas Palmeira Ferraz, Bruno Veloso, Anna Helena Reali Costa
- Anthology ID:
- 2024.propor-1.50
- Volume:
- Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1
- Month:
- March
- Year:
- 2024
- Address:
- Santiago de Compostela, Galicia/Spain
- Editors:
- Pablo Gamallo, Daniela Claro, António Teixeira, Livy Real, Marcos Garcia, Hugo Gonçalo Oliveira, Raquel Amaro
- Venue:
- PROPOR
- SIG:
- Publisher:
- Association for Computational Lingustics
- Note:
- Pages:
- 492–502
- Language:
- URL:
- https://aclanthology.org/2024.propor-1.50
- DOI:
- Cite (ACL):
- Alexandre Alcoforado, Lucas Hideki Takeuchi Okamura, Israel Campos Fama, Bárbara Fernandes Dias Bueno, Arnold Moya Lavado, Thomas Palmeira Ferraz, Bruno Veloso, and Anna Helena Reali Costa. 2024. From Random to Informed Data Selection: A Diversity-Based Approach to Optimize Human Annotation and Few-Shot Learning. In Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1, pages 492–502, Santiago de Compostela, Galicia/Spain. Association for Computational Lingustics.
- Cite (Informal):
- From Random to Informed Data Selection: A Diversity-Based Approach to Optimize Human Annotation and Few-Shot Learning (Alcoforado et al., PROPOR 2024)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2024.propor-1.50.pdf