Robustness of Retrieval-Augmented Generation Models Across Corpus Sizes on NaturalQuestions
Abstract
This report synthesises findings from 12 peer-reviewed papers addressing the following research question: What is the impact of varying the size of the document corpus on the robustness of Retrieval-Augmented Generation models on the NaturalQuestions benchmark when evaluated using F1 score. 14 claims were extracted from source literature; 12 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.5/10. This report is a machine-generated literature synthesis and does not constitute original research. Research goal: What is the impact of varying the size of the document corpus on the robustness of Retrieval-Augmented Generation models on the NaturalQuestions benchmark when evaluated using F1 score? Autonomous literature synthesis. Automated review score: 8.5/10. Full text and citation available at Assignee Research.
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