The field of mental health support is undergoing a significant transformation with the integration of Artificial Intelligence (AI) and Large Language Models (LLMs). Recent developments have focused on creating more empathetic and personalized support systems, moving beyond generic responses to provide tailored assistance to individuals in need. Noteworthy papers in this area have introduced innovative approaches, such as integrating diagnostic and therapeutic reasoning with LLMs, and developing self-evolution frameworks for user preference alignment. These advancements have the potential to revolutionize mental health counseling, enabling more effective and compassionate support for individuals struggling with mental health issues. Notable research includes the development of PsyLLM, a large language model designed to integrate diagnostic and therapeutic reasoning for mental health counseling, and the introduction of a self-evolution framework that helps LLMs improve their responses to better align with users' implicit preferences. The DecoupledESC framework has also shown promise in enhancing emotional support generation via strategy-response decoupled preference optimization.