CUE-R: Beyond the Final Answer in Retrieval-Augmented Generation
As language models shift from single-shot answer generation toward multi-step reasoning that retrieves and consumes evidence mid-inference, evaluating the role of individual retrieved items becomes more important. Existing RAG evaluation typically targets final-answer quality, citation faithfulness, or answer-level attribution, but none of these directly targets the intervention-based, per-evidence-item utility view we study here. We introduce CUE-R, a lightweight intervention-based framework for measuring per-evidence-item operational utility in single-shot RAG using shallow observable retrieval-use traces. CUE-R perturbs individual evidence items via REMOVE, REPLACE, and DUPLICATE opera...
| Authors | Siddharth Jain, Venkat Narayan Vedam |
|---|---|
| Primary category | cs.IR |
| Published | 7 April 2026 |
| Last updated at source | 7 April 2026 |
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