The Cognitive Categorical Transformer (CCT) significantly improves language modeling performance by integrating category theory concepts into a 306M-parameter architecture, achieving a 12% reduction in perplexity compared to a fine-tuned GPT-2 Small. This advancement highlights the potential of cognitive science-inspired techniques in enhancing AI language models.