A Survey on Explainability in Machine Reading Comprehension
It provides a comprehensive survey for researchers in MRC, but is incremental as it synthesizes existing work without new results.
This paper systematically reviews benchmarks, approaches, and evaluation methodologies for explainability in Machine Reading Comprehension, identifying open research questions and future directions.
This paper presents a systematic review of benchmarks and approaches for explainability in Machine Reading Comprehension (MRC). We present how the representation and inference challenges evolved and the steps which were taken to tackle these challenges. We also present the evaluation methodologies to assess the performance of explainable systems. In addition, we identify persisting open research questions and highlight critical directions for future work.