Entropy-Based Measurement of Value Drift and Alignment Work in Large Language Models

This article likely discusses a novel method for assessing how the values encoded in large language models (LLMs) change over time (value drift) and how well these models are aligned with human values. The use of entropy suggests a focus on the uncertainty or randomness in the model's outputs, potentially to quantify deviations from desired behavior. The source, ArXiv, indicates this is a research paper, likely presenting new findings and methodologies.