Trust, but Don't Verify: Epistemic Blind Spots in LLM Source Evaluation
Language models increasingly act as epistemic proxies, synthesizing evidence from multiple sources to inform decisions. Whether they evaluate the quality of that evidence, or merely aggregate it based on surface presentation, remains poorly understood. We show that models possess the capability to detect fabricated statistics in isolation but do not recruit this capability during multi-source synthesis, producing similar numeric estimates whether the statistics are fabricated or valid. Specifically, source influence is governed by a methodology-register gate that responds to the distributional register of analytical text but not to numeric validity: for example, statistically impossible c...
| Authors | Rohan N. Pradhan, Steve Goley |
|---|---|
| Primary category | cs.LG |
| Published | 3 June 2026 |
| Last updated at source | 8 July 2026 |
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