The field of compositional generalization is currently experiencing a renaissance in AI, as novel problem settings and algorithms motivated by various practical applications are being introduced, building on top of the classical compositional generalization problem. This article aims to provide a comprehensive review of top recent developments in multiple real-life applications of the compositional generalization. Specifically, we introduce a taxonomy of common applications and summarize the state-of-the-art for each of those domains. Furthermore, we identify important current trends and provide new perspectives pertaining to the future of this burgeoning field.

翻译：组合泛化领域当前正经历着人工智能领域的复兴，基于经典组合泛化问题，各类由实际应用驱动的新问题设定与算法不断涌现。本文旨在系统综述组合泛化在多个现实应用场景中的前沿进展，具体而言，我们构建了常见应用场景的分类体系，并总结了每个领域的最新技术水平。此外，我们识别了当前重要趋势，并为这一蓬勃发展领域的未来提供了新视角。