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The document presents a multi-task prediction-powered inference (PPI) framework aimed at improving statistical inference across related tasks in AI evaluation and social science research, particularly when high-quality labels are scarce. It introduces methods that leverage shared structures in proxy-ground-truth relationships to enhance inferential power while maintaining task-specific validity. A case study on the 2024 U.S. presidential election demonstrates the effectiveness of these methods in reducing c

Author

sherin0782

Language

EN