Abstract
The BioLaySumm 2024 shared task at the ACL 2024 BioNLP workshop aims to transform biomedical research articles into lay summaries suitable for a broad audience, including children. We utilize the BioBART model, designed for the biomedical sector, to convert complex scientific data into clear, concise summaries. Our dataset, which includes a range of scientific abstracts, enables us to address the diverse information needs of our audience. This focus ensures that our summaries are accessible to both general and younger lay audience. Additionally, we employ specialized tokens and augmentation techniques to optimize the model’s performance. Our methodology proved effective, earning us the 7th rank on the final leaderboard out of 57 participants.- Anthology ID:
- 2024.bionlp-1.73
- Volume:
- Proceedings of the 23rd Workshop on Biomedical Natural Language Processing
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Dina Demner-Fushman, Sophia Ananiadou, Makoto Miwa, Kirk Roberts, Junichi Tsujii
- Venues:
- BioNLP | WS
- SIG:
- SIGBIOMED
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 793–803
- Language:
- URL:
- https://aclanthology.org/2024.bionlp-1.73
- DOI:
- Cite (ACL):
- Loukritia Stefanou, Tatiana Passali, and Grigorios Tsoumakas. 2024. AUTH at BioLaySumm 2024: Bringing Scientific Content to Kids. In Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, pages 793–803, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- AUTH at BioLaySumm 2024: Bringing Scientific Content to Kids (Stefanou et al., BioNLP-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.bionlp-1.73.pdf