Abstract: In this paper, we consider the model merging process for large language models (LLMs) under a two-stage optimization framework. Traditional merging methods usually apply fixed blending rates ...

The ongoing massive investments in artificial intelligence (AI) aim to satisfy a huge increase in anticipated demand, which in turn has led some firms to offer rosy growth forecasts. To assess these ...

Abstract: We present an information-theoretic approach to quantum state classification based on sequential Bayesian inference. In each measurement step, the algorithm updates a probability ...