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A Survey on Explainability in Machine Reading Comprehension

arXiv 2010.00389 ↗First posted 1 Oct 2020cs.CL cs.AIcited by 33

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Abstract (arXiv)

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.

Key facts. Cited by 33 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Oct 2020.

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Citing papers per year: 2021: 9; 2022: 12; 2023: 5; 2024: 6; 2025: 1.

33 papers.

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  1. 2021Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processingcited by 126
  2. 2023Rationalization for Explainable NLP: A Surveycited by 22
  3. 2021Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violencecited by 19
  4. 2021Hybrid Autoregressive Inference for Scalable Multi-hop Explanation Regenerationcited by 17
  5. 2022METGEN: A Module-Based Entailment Tree Generation Framework for Answer Explanationcited by 17
  6. 2023Faithful Question Answering with Monte-Carlo Planningcited by 16
  7. 2024Enhancing Ethical Explanations of Large Language Models through Iterative Symbolic Refinementcited by 16
  8. 2022Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-makingcited by 14
  9. 2021Do Natural Language Explanations Represent Valid Logical Arguments? Verifying Entailment in Explainable NLI Gold Standardscited by 12
  10. 2021Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehensioncited by 10
  11. 2022Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoningcited by 8
  12. 2021Diff-Explainer: Differentiable Convex Optimization for Explainable Multi-hop Inferencecited by 7
21 more
  1. 2024Improving Semantic Control in Discrete Latent Spaces with Transformer Quantized Variational Autoencoderscited by 6
  2. 2021On the Challenges of Evaluating Compositional Explanations in Multi-Hop Inference: Relevance, Completeness, and Expert Ratingscited by 5
  3. 2022A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology datacited by 5
  4. 2023HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervisioncited by 5
  5. 2024Inference to the Best Explanation in Large Language Modelscited by 5
  6. 2021Encoding Explanatory Knowledge for Zero-shot Science Question Answeringcited by 3
  7. 2021Generating Hypothetical Events for Abductive Inferencecited by 3
  8. 2022Do Transformers Encode a Foundational Ontology? Probing Abstract Classes in Natural Languagecited by 3
  9. 2024SEER: Facilitating Structured Reasoning and Explanation via Reinforcement Learningcited by 3
  10. 2022SuMe: A Dataset Towards Summarizing Biomedical Mechanismscited by 2
  11. 2023Machine Reading Comprehension using Case-based Reasoningcited by 2
  12. 2022Scientific Explanation and Natural Language: A Unified Epistemological-Linguistic Perspective for Explainable AIcited by 1
  13. 2022Going Beyond Approximation: Encoding Constraints for Explainable Multi-hop Inference via Differentiable Combinatorial Solverscited by 1
  14. 2022A Comprehensive Survey on Multi-hop Machine Reading Comprehension Datasets and Metricscited by 1
  15. 2022A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approachescited by 1
  16. 2023Towards Controllable Natural Language Inference through Lexical Inference Typescited by 1
  17. 2024A Differentiable Integer Linear Programming Solver for Explanation-Based Natural Language Inferencecited by 1
  18. 2022Active entailment encoding for explanation tree construction using parsimonious generation of hard negativescited by 0
  19. 2022Accountable and Explainable Methods for Complex Reasoning over Textcited by 0
  20. 2024CARE: A Clue-guided Assistant for CSRs to Read User Manualscited by 0
  21. 2025Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncodercited by 0