An intuitionistic fuzzy set annotation scheme is claimed to raise inter-annotator agreement from 0.67 to 0.79, cut annotation time by 15.7%, and improve RLHF win rate by 12.3%, but without released artifacts or significance testing.
Clark et al., ”All that’s ’human’ is not gold: Evaluati ng human evaluation of generated text,” in Proc
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Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling
An intuitionistic fuzzy set annotation scheme is claimed to raise inter-annotator agreement from 0.67 to 0.79, cut annotation time by 15.7%, and improve RLHF win rate by 12.3%, but without released artifacts or significance testing.