Symbolic augmentation closes a canonical-equivalence blind spot in neural fact-checkers
Read the original at arxiv.org→arXiv:2607.16212v1 Announce Type: new Abstract: Large language models hallucinate numbers and units when summarizing scientific text, a failure mode that can silently invert a scientific claim. We recast the...
Original headline: "Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers"