mlsanityData to 7 Oct 2026

UNCC Biomedical Semantic Question Answering Systems. BioASQ: Task-7B, Phase-B

arXiv 2002.01984 ↗First posted 5 Feb 2020cs.CL cs.IRcited by 1

Not on the map. Why?

Abstract (arXiv)

In this paper, we detail our submission to the 2019, 7th year, BioASQ competition. We present our approach for Task-7b, Phase B, Exact Answering Task. These Question Answering (QA) tasks include Factoid, Yes/No, List Type Question answering. Our system is based on a contextual word embedding model. We have used a Bidirectional Encoder Representations from Transformers(BERT) based system, fined tuned for biomedical question answering task using BioBERT. In the third test batch set, our system achieved the highest MRR score for Factoid Question Answering task. Also, for List type question answering task our system achieved the highest recall score in the fourth test batch set. Along with our detailed approach, we present the results for our submissions, and also highlight identified downsides for our current approach and ways to improve them in our future experiments.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 5 Feb 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2022: 1.

1 paper.