Summary of Stratified Prediction-powered Inference For Hybrid Language Model Evaluation, by Adam Fisch et al.
Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation
by Adam Fisch, Joshua Maynez, R. Alex Hofer, Bhuwan Dhingra, Amir Globerson, William W. Cohen
First submitted to arxiv on: 6 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Machine Learning (stat.ML)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Prediction-powered inference (PPI) is a method that enhances statistical estimates by combining small amounts of human-labeled data with larger amounts of data labeled by an automatic system, resulting in tighter confidence intervals. This paper proposes Stratified Prediction-Powered Inference (StratPPI), which improves upon basic PPI estimates using simple data stratification strategies. The algorithm is based on stratified sampling and provides provably valid confidence intervals for population parameters without making assumptions about the underlying automatic labeling system or data distribution. Empirical results show that StratPPI can provide substantially tighter confidence intervals than unstratified approaches, especially when the performance of the autorater varies across conditional distributions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to predict how well a computer program will work based on some data. But the data is limited because it was labeled by humans, which can be time-consuming and expensive. This paper introduces a new way to improve those predictions by combining small amounts of human-labeled data with larger amounts of data labeled by computers. The new method, called Stratified Prediction-Powered Inference (StratPPI), can provide more accurate results than previous methods. It works by sorting the data into different groups and then using those groups to make better predictions. |
Keywords
» Artificial intelligence » Inference
