Relevance Is Not Sufficient Evidence: Detecting Evidence Gaps Before Generation in RAG
Retrieval-augmented generation (RAG) grounds large language models in external sources, but retrieved passages often name the right entities without providing the facts needed to answer. Even when instructed to abstain, 12 generators answer 40.0-99.3% of insufficient-evidence questions. Training generators to abstain ties the decision to model weights, may reward answers recalled from parametric knowledge, and still requires a full generator call. Can sufficiency be judged from the question and evidence alone, before any answer exists? We identify pitfalls in constructing insufficient-evidence tests: removing relevant evidence or pairing evidence with unrelated questions can reveal labels...
| Authors | Suting Chen, Peichun Hua, Yunming Xiao |
|---|---|
| Primary category | cs.CL |
| Published | 27 September 2026 |
| Last updated at source | 27 September 2026 |
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