BLADE: Distilled LLM Regularization for Calibrated Knowledge Graph Completion
BLADE is presented, a variational model that separates latent truth from graph recording and distills offline language-model judgments into a frozen teacher regularizer and claims calibration only for the declared candidate distributions, not for all unobserved triples.
Ibne Farabi Shihab, Rabeya Bosri Tamanna, Abdo El Karaky et al.
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