Learning When to Trust LLM Priors: A Validated Framework for Semantic Prior Integration
arXiv:2601.21410v3 Announce Type: replace
Abstract: Large language models (LLMs) encode rich semantic knowledge that can be useful for supervised learning, but their outputs are unreliable as statistical priors: they may be noisy, misspecified, or hal…