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In recent years, the rapid advancement and impressive capabilities of LargeLanguage Models (LLMs) have been evident across various domains. This paperexplores the application, implications, and potential of LLMs in buildingenergy efficiency and decarbonization studies. The wide-ranging capabilities ofLLMs are examined in the context of the building energy field, includingintelligent control systems, code generation, data infrastructure, knowledgeextraction, and education. Despite the promising potential of LLMs, challengesincluding complex and expensive computation, data privacy, security andcopyright, complexity in fine-tuned LLMs, and self-consistency are discussed.The paper concludes with a call for future research focused on the enhancementof LLMs for domain-specific tasks, multi-modal LLMs, and collaborative researchbetween AI and energy experts.

Opportunities and Challenges of Applying Large Language Models in Building Energy Efficiency and Decarbonization Studies: An Exploratory Overview