Enhancing Abstraction in Large Language Models Through Nature-Inspired Semantic Patterns

Recent advancements in artificial intelligence emphasize improving the abstraction capabilities of Large Language Models (LLMs) by integrating structured knowledge and sophisticated neural architectures. This paper proposes a novel approach grounded in a