State-of-the-Art Approaches

This chapter performs a thorough assessment and meticulous examination of the most advanced EA techniques. Initially, we introduce a broad EA framework that covers all current methods and classify these methods into three main groups. Then, we carefully appraise these solutions on various scenarios, taking into account their efficacy, efficiency, and scalability. Lastly, we create a novel EA dataset that reflects the actual difficulties encountered in alignment, which prior literature mostly ignored. This chapter aims to offer a comprehensive understanding of the advantages and drawbacks of current EA methods, in order to encourage further high-quality research.