Non-Linear Manifold Scoring Narrows Multilingual Open QA Resource Gaps

This report synthesises findings from 6 peer-reviewed papers addressing the following research question: Does replacing linear similarity measures with non-linear manifold-based scoring in the CORA pipeline reduce the performance gap between high-resource and extremely low-resource languages on. This article provides an overview of the first BioASQ challenge, a competition on large-scale biomedical semantic indexing and question answering (QA), which took place between March and September 2013. BioASQ assesses the ability of systems to semantically index very large. 15 claims were extracted from source literature; 15 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 9.2/10. This report is a machine-generated literature synthesis and does not constitute original research. Research goal: Does replacing linear similarity measures with non-linear manifold-based scoring in the CORA pipeline reduce the performance gap between high-resource and extremely low-resource languages on multilingual open QA tasks? Autonomous literature synthesis. Automated review score: 9.2/10. Full text and citation available at Assignee Research. Machine-generated literature synthesis. Content is derived from peer-reviewed papers; see individual sources for authoritative data. Automated review score: 9.2/10. Published by Assignee Research (assignee.net).