Papers with human-centered evaluation metrics

1 papers
Annotator-Centric Active Learning for Subjective NLP Tasks (2024.emnlp-main)

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Challenge: Annotator-centric active learning addresses the high costs of collecting human annotations by strategically annotating the most informative samples.
Approach: They propose annotator-centric active learning which incorporates an annotation strategy following data sampling to approximate the full diversity of human judgments.
Outcome: The proposed approach improves data efficiency and performs well in annotator-centric evaluations.

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