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0111 · Jun 202419922001200920172026
3 results for autorater

Efficiently evaluate generative models at the prompt level using tensor factorization.

problem Fine-grained evaluations of generative models are costly and often misaligned with human judgment.
method Tensor factorization model that merges cheap autorater data with a small set of human gold-standard labels.
result The method provides accurate and tight confidence intervals for model performance.

StratPPI improves prediction-powered inference with stratified sampling.

problem Improving statistical estimates with limited human-labeled data.
method Combining small human-labeled data with large automatic-labeled data, stratifying data for tighter confidence intervals.
result StratPPI provides substantially tighter confidence intervals than unstratified approaches.