# Topic Judge

Topic models can describe topics with interpretable directions learned by sparse autoencoders instead of word lists, and an LLM-based topic judge prefers that representation on eight datasets, with the largest margins on short and abstract texts.

Topic models can describe topics with interpretable directions learned by sparse autoencoders instead of word lists, and an LLM-based topic judge prefers that representation on eight datasets, with the largest margins on short and abstract texts.