Active Learning with Multiple Annotators

Multi-annotator Active Learning

Machine learning paradigm where multiple annotators collaborate to label the most informative data selected by an active algorithm. This approach optimizes the use of human resources by leveraging complementary expertise and variable annotator costs.

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