Download Dataset
You can find dataset and instructions here.
Leaderboard 🏆
You can find the leaderboard for question answering and dense passage retrieval here.
About WISEST-QA Dataset
The WISEST-QA dataset represents a pioneering advancement in biomedical question answering and systematic review assessment. This dataset uniquely represents the insights by answering two renowned systematic review assessment tools—ROBIS and AMSTAR2—with detailed annotations to challenge and refine machine learning models aimed at understanding complex biomedical literature. The dataset consists of a diverse range of questions derived from actual systematic reviews. By providing annotated data on the quality and reliability of systematic reviews, it serves as a critical resource for developing models for diverse natural language processing tasks such as question answering and dense passage retrieval. WISEST-QA not only addresses the lack of systematic review assessment datasets in the information retrieval community but also sets a new benchmark for question-answering models by introducing a challenging natural language understanding task. This dataset is expected to catalyze advancements in question-answering algorithms, especially AI applications for evidence-based medicine, facilitating improved decision-making in clinical settings and research.
Meet Our Team
Our comprehensive suite of professionals caters to a diverse team.
Associate Professor at University of Toronto
Canada Research Chair in Knowledge Synthesis
Director at Unity Health Toronto
Principal Investigator
Professor at Toronto Metropolitan University
Canada Research Chair in Social Information Retrieval
NSERC Industrial Research Chair
A.I. Specialist
Kevin Sun
Data Scientist