ConflictScore: Identifying and Measuring How Language Models Handle Conflicting Evidence
Existing metrics for factuality and faithfulness evaluate whether an answer is supported or contradicted by its grounding documents, but they fail to capture when both supporting and contradicting evidence coexist. We introduce ConflictScore, a novel metric that quantifies how well a model's response acknowledges conflicting evidence in its grounding documents. Our framework decomposes responses into atomic claims, labels each claim against each grounding document, and then aggregates these labels into two complementary measures: ConflictScore-Count (CS-C), the proportion of claims exhibiting conflicts, and ConflictScore-Ratio (CS-R), the balance between supporting and contradicting evide...
| Authors | Siyi Liu, Aaron Halfaker, Dan Roth et al. |
|---|---|
| Primary category | cs.CL |
| Published | 24 June 2026 |
| Last updated at source | 24 June 2026 |
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