IITR at BioLaySumm Task 1:Lay Summarization of BioMedical articles using Transformers

Venkat praneeth Reddy, Pinnapu Reddy Harshavardhan Reddy, Karanam Sai Sumedh, Raksha Sharma


Abstract
Initially, we analyzed the datasets in a statistical way so as to learn about various sections’ contributions to the final summary in both the pros and life datasets. We found that both the datasets have an Introduction and Abstract along with some initial parts of the results contributing to the summary. We considered only these sections in the next stage of analysis. We found the optimal length or no of sentences of each of the Introduction, abstract, and result which contributes best to the summary. After this statistical analysis, we took the pre-trained model Facebook/bart-base and fine-tuned it with both the datasets PLOS and eLife. While fine-tuning and testing the results we have used chunking because the text lengths are huge. So to not lose information due to the number of token constraints of the model, we used chunking. Finally, we saw the eLife model giving more accurate results than PLOS in terms of readability aspect, probably because the PLOS summary is closer to its abstract, we have considered the eLife model as our final model and tuned the hyperparameters. We are ranked 7th overall and 1st in readability
Anthology ID:
2023.bionlp-1.67
Volume:
The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Dina Demner-fushman, Sophia Ananiadou, Kevin Cohen
Venue:
BioNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
625–628
Language:
URL:
https://aclanthology.org/2023.bionlp-1.67
DOI:
10.18653/v1/2023.bionlp-1.67
Bibkey:
Cite (ACL):
Venkat praneeth Reddy, Pinnapu Reddy Harshavardhan Reddy, Karanam Sai Sumedh, and Raksha Sharma. 2023. IITR at BioLaySumm Task 1:Lay Summarization of BioMedical articles using Transformers. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 625–628, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
IITR at BioLaySumm Task 1:Lay Summarization of BioMedical articles using Transformers (Reddy et al., BioNLP 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.bionlp-1.67.pdf