AI RESEARCH
Conformal Path Reasoning: Trustworthy Knowledge Graph Question Answering via Path-Level Calibration
arXiv CS.CL
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ArXi:2605.08077v1 Announce Type: new Knowledge Graph Question Answering (KGQA) has shown promise for grounded and interpretable reasoning, yet existing approaches often fail to provide reliable coverage guarantees over retrieved answers. While Conformal Prediction (CP) offers a principled framework for producing prediction sets with statistical guarantees, prior methods suffer from critical limitations in both calibration validity and score discriminability, resulting in violated coverage guarantees and excessively large prediction sets.