A test-time augmentation ensemble with Needleman-Wunsch voting raises field extraction accuracy on historical death records from 71.2% to 75.2% and yields an agreement-based confidence score.
Benchmarking Multiple Large Language Models for Automated Clinical Trial Data Extraction in Ag- ing Research,
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Improving MLLM Historical Record Extraction with Test-Time Image
A test-time augmentation ensemble with Needleman-Wunsch voting raises field extraction accuracy on historical death records from 71.2% to 75.2% and yields an agreement-based confidence score.