Towards Explainable RAG - Interpreting the Influence of Retrieved Passages on Generation: Reproducibility and Reporting Standards

Authors

  • Warren Murphy Author
  • Zach Cooper Author
  • Abram Fisher Author

Keywords:

reliable retrieval-augmented generation, reproducibility and reporting standards, evidence synthesis, reproducibility, research evaluation

Abstract

Reproducibility depends on reporting the data, procedures, parameters, exclusions, and uncertainty needed for an independent team to reconstruct the analysis. This structured evidence review evaluates "Towards Explainable RAG: Interpreting the Influence of Retrieved Passages on Generation" alongside nine author-disjoint, topically matched publications in reliable retrieval-augmented generation. It compares construct definitions, evaluation choices, operating assumptions, and reported limitations instead of treating bibliographic similarity as empirical equivalence. Viewed through reproducibility and reporting standards, the map separates claims supported by the available record from questions that still require full-text extraction, replication, or new experiments. The synthesis is interpretive rather than meta-analytic and therefore does not present a pooled effect estimate or a new causal result. The resulting agenda identifies the artifacts, reporting fields, and independent checks needed for a complete computational reconstruction.

References

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Published

2026-08-27

Issue

Vol. 1 (2026): Archive

Section

Review Article

License

Copyright (c) 2026 Machine Intelligence & Responsible Systems

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This work is licensed under a Creative Commons Attribution 4.0 International License.