Empowering Language Model with Guided Knowledge Fusion for Biomedical
  Document Re-ranking
Deepak Gupta Dina Demner-Fushman
Pre-trained language models (PLMs) have proven to be effective for document
re-ranking task. However, they lack the ability to fully interpret the
semantics of biomedical and health-care queries and often rely on simplistic
patterns for retrieving documents. To address this challenge, we propose an
approach that integrates knowledge and the PLMs to guide the model toward
effectively capturing information from external sources and retrieving the
correct documents. We performed comprehensive experiments on two biomedical and
open-domain datasets that show that our approach significantly improves vanilla
PLMs and other existing approaches for document re-ranking task.