EviGraph: proof-carrying selective recommendation over temporal public-service knowledge graphs (arXiv:2610.00212v1)
This paper introduces EviGraph, a system that separates critical decision requirements from noncritical unknowns by having a language agent link required criteria to evidence in a temporal knowledge graph and a deterministic checker verify whether a recommendation is supported. Evaluation on a bilingual Hong Kong public-service benchmark with executable policy references shows the approach reduces unnecessary abstention, while additional verification steps can sometimes revoke supported recommendations without improving decision outcomes.