A composite abstention architecture combining instruction prompting and a support-deficit gate from three black-box signals reduces hallucinations more effectively than either component alone across tested models and regimes.
Language models are few-shot learners
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Hallucination as output-boundary misclassification: a composite abstention architecture for language models
A composite abstention architecture combining instruction prompting and a support-deficit gate from three black-box signals reduces hallucinations more effectively than either component alone across tested models and regimes.