Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments

Researchers developed a method to improve app store search relevance by using large language models to generate textual relevance judgments, addressing the scarcity of expert-labeled data. A specialized fine-tuned model significantly outperformed general-purpose LLMs in evaluating semantic fit between queries and results.