AUEB at BioASQ 6: Document and Snippet Retrieval
Not on the map. Why?
Abstract (arXiv)
We present AUEB's submissions to the BioASQ 6 document and snippet retrieval tasks (parts of Task 6b, Phase A). Our models use novel extensions to deep learning architectures that operate solely over the text of the query and candidate document/snippets. Our systems scored at the top or near the top for all batches of the challenge, highlighting the effectiveness of deep learning for these tasks.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Sep 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 3; 2022: 1; 2023: 1.
5 papers.
- 2021Biomedical Question Answering: A Survey of Approaches and Challengescited by 46
- 2022Data Augmentation for Biomedical Factoid Question Answeringcited by 5
- 2021A Neural Model for Joint Document and Snippet Ranking in Question Answering for Large Document Collectionscited by 2
- 2021Recent Advances in Automated Question Answering In Biomedical Domaincited by 0
- 2023Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-rankingcited by 0
- 2023Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-ranking7 May 2023
- 2022Data Augmentation for Biomedical Factoid Question Answering10 Apr 2022
- 2021Recent Advances in Automated Question Answering In Biomedical Domain10 Nov 2021
- 2021A Neural Model for Joint Document and Snippet Ranking in Question Answering for Large Document Collections16 Jun 2021
- 2021Biomedical Question Answering: A Survey of Approaches and Challenges10 Feb 2021