Predictive Human Preference: From Model Ranking to Model Routing
Read OriginalThis article discusses the concept of predictive human preference for AI model selection and routing. It examines how human preference data, like that from LMSYS's Chatbot Arena, can be used to predict which model (e.g., GPT-4 vs. Claude Instant) a user would prefer for a specific prompt. The piece covers use cases like cost-effective model routing and model interpretability, and outlines methods for building a preference predictor.
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