The Temperature Behind Ratings: Using LLMs to Make Recommendations That Are Just a Cut Above

The recommendation and AI teams used an LLM to score restaurant reviews more precisely, then distilled that judgment into ELECTRA for production use.

The goal was to find truly high-satisfaction restaurants even among reviews with inflated ratings.

By capturing review authenticity and subtle quality differences beyond star ratings, the system reduces user verification effort and improves recommendation accuracy.