Unlike previous pipelined approaches, RE 3 QA shares contextualized text representation across different components, and is carefully designed to use high-quality upstream outputs (e.g., retrieved context or candidate answers) for directly supervising downstream modules (e.g., the reader or the reranker).
the whole network can be trained end-to-end to avoid the context inconsistency problem.