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

Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments arXiv:2602.23234v4 Announce Type: replace-cross Abstract: Large-scale commercial search systems optimize for relevance to drive successful sessions that help users find what they are looking for. To maximize relevance, we leverage two complementary objectives: behavioral relevance (results users tend to click or download) and textual relevance (a result's semantic fit to the query). A persistent challenge is the