Enhancing Building Semantics Preservation in AI Model Training with Large Language Model Encodings.

This research investigates methods to improve the preservation of building semantics during the training of AI models, utilizing large language model encodings. It aims to create more intelligent and context-aware AI systems for applications in architecture, urban planning, and smart building management.