Papers with annotator-reliability-based soft-label aggregation

1 papers
Efficient Annotator Reliability Assessment with EffiARA (2025.acl-demo)

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Challenge: Obtaining annotations from experts is ideal, but this expertise is logistically and financially costly.
Approach: They propose an annotation framework that supports the whole annotation pipeline from understanding the resources required for an annotation task to compiling the annotated dataset.
Outcome: The proposed framework improves classification performance through annotator-reliability-based soft-label aggregation and sample weighting, and increases agreement among annotators through removal of identifying and replacing an unreliable annotation.

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