SOURCE-LINKED INTELLIGENCE
EviScope: Paired Counterfactual Evidence Diagnostics for Faithful and Efficient Grounded Language Models
Grounded language-model systems are often evaluated by final answer accuracy, yet a correct answer can be unsupported, drawn from the wrong source, or produced when evidence is insufficient or contradictory. We introduce EviScope, a paired counterfactual benchmark that holds the question fixed while adding, removing, distracting, or contradicting its evidence. EviScope-v1.1 contains 40 four-condition quartets with repaired counterfactual claims and span-level support labels for automatic evaluation. Across 960 gold-blind generations from Qwen2.5-7B, Llama 3.1 8B, and Gemini 3.5 Flash, paired m
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T12:18:19.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.