IGGQ Research Publishing
Machine Intelligence & Responsible Systems

Towards Explainable RAG - Interpreting the Influence of Retrieved Passages on Generation: Evaluation Design and Construct Validity

Abstract

Evaluation is persuasive only when the measured outcome corresponds to the construct claimed by the study and the comparison answers the stated research question. 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 evaluation design and construct validity, 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 aligns claims, outcomes, comparators, sampling, and uncertainty before any performance estimate is interpreted.

Keywords
reliable retrieval-augmented generationevaluation design and construct validityevidence synthesisreproducibilityresearch evaluation
References
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Publication details
Journal
Machine Intelligence & Responsible Systems
Volume
1 (2026)
Article number
mi20260028
License
CC BY 4.0