Semantic Information Theory: A Complete Mathematical Framework Unifying Meaning and Information
A landmark extension of Shannon's information theory to semantic content. We formalize 'semantic information' as a measurable quantity distinct from syntactic entropy, prove rate-distortion bounds for meaning-preserving compression, and establish the theoretical foundations for cross-model AI communication.