<ul data-eligibleForWebStory="true"><li>Introduces quantum-inspired framework to analyze trade-off in language models - SIUP.</li><li>Derives Semantic-Information Uncertainty Principle (SIUP) bounding semantic drift and factual accuracy trade-off.</li><li>Provides regularization techniques, algorithms, and interpretability methods for large language models.</li><li>Empirical analysis and theoretical foundations support the validity and applications of the framework.</li></ul>

The Semantic-Information Uncertainty Principle: A Quantum-Inspired Framework for Understanding…

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