BioASQ
Related Papers
A tool suite for creating question answering benchmarks
AbstractWe introduce the BIOASQ suite, a set of open-source Web tools for the creation, assessment and community-driven improvement of question answering benchmarks. The suite comprises three main tools: (1) the …...
Neural Domain Adaptation for Biomedical Question Answering
AbstractFactoid question answering (QA) has recently benefited from the development of deep learning (DL) systems. Neural network models outperform traditional approaches in domains where large datasets exist, such as SQuAD …...
BioMedBERT: A Pre-trained Biomedical Language Model for QA and IR
AbstractThe SARS-CoV-2 (COVID-19) pandemic spotlighted the importance of moving quickly with biomedical research. However, as the number of biomedical research papers continue to increase, the task of finding relevant articles …...
A Neural Model for Joint Document and Snippet Ranking in Question Answering for Large Document Collections
AbstractQuestion answering (QA) systems for large document collections typically use pipelines that (i) retrieve possibly relevant documents, (ii) re-rank them, (iii) rank paragraphs or other snippets of the top-ranked documents, …...
Learning to Generate Questions by Learning to Recover Answer-containing Sentences
To train a question answering model based on machine reading comprehension (MRC), sig- nificant effort is required to prepare annotated training data composed of questions and their answers from contexts. …...
Task-adaptive Pre-training of Language Models with Word Embedding Regularization
Pre-trained language models (PTLMs) ac- quire domain-independent linguistic knowl- edge through pre-training with massive textual resources. Additional pre-training is effective in adapting PTLMs to domains that are not well covered …...
LinkBERT: Pretraining Language Models with Document Links
AbstractLanguage model (LM) pretraining captures various knowledge from text corpora, helping downstream tasks. However, existing methods such as BERT model a single document, and do not capture dependencies or knowledge …...
Unsupervised Question Answering via Answer Diversifying
AbstractUnsupervised question answering is an attractive task due to its independence on labeled data. Previous works usually make use of heuristic rules as well as pre-trained models to construct data …...