A multi-agent hierarchical Bayesian model corrects selection bias in LLM user feedback via topic clustering and reweighting with mild priors on the feedback channel to recover accurate aggregate quality estimates.
UltraFeedback: Boosting language models with scaled AI feedback
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Correcting Selection Bias in Sparse User Feedback for Large Language Model Quality Estimation: A Multi-Agent Hierarchical Bayesian Approach
A multi-agent hierarchical Bayesian model corrects selection bias in LLM user feedback via topic clustering and reweighting with mild priors on the feedback channel to recover accurate aggregate quality estimates.