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This paper offers a comprehensive synthesis of Reasoning Shortcuts (RSs) in Neuro-Symbolic (NeSy) AI, a phenomenon where models achieve high prediction accuracy by incorrectly grounding internal symbolic concepts. It unifies theoretical insights into RSs, categorizes practical strategies for their mitigation and detection, and outlines future research to foster the development of more trustworthy and interpretable NeSy systems.