A new study introduces a cognitive benchmarking framework designed to evaluate how large language models (LLMs) handle culturally specific knowledge. By combining Bloom's Taxonomy with Retrieval-Augmented Generation, this framework assesses LLM performance across various cognitive domains, including Remembering and Creating. This is significant as it not only enhances our understanding of LLM capabilities but also ensures that these models can effectively engage with diverse cultural contexts, making them more relevant and useful in real-world applications.