Ensemble Diversity Optimization jointly learns ensemble weights, size, and a signed diversity regularizer, substantially improving calibration to annotator distributions on subjective text classification.
Modeling Annotator Perspective and Polarized Opinions to Improve Hate Speech Detection
3 Pith papers cite this work, alongside 51 external citations. Polarity classification is still indexing.
3
Pith papers citing it
51
external citations · OpenAlex
representative citing papers
Agreement-based clustering of annotators improves performance on subjective NLP tasks by capturing diverse perspectives better than majority voting or per-annotator modeling.
Proposes and illustrates a community-informed, multi-perspective approach to developing AI for analyzing LAPD body-worn camera footage of traffic stops.
citing papers explorer
-
Ensemble Diversity Optimization for Subjective Supervision
Ensemble Diversity Optimization jointly learns ensemble weights, size, and a signed diversity regularizer, substantially improving calibration to annotator distributions on subjective text classification.
-
Beyond Majority Voting: Agreement-Based Clustering to Model Annotator Perspectives in Subjective NLP Tasks
Agreement-based clustering of annotators improves performance on subjective NLP tasks by capturing diverse perspectives better than majority voting or per-annotator modeling.
-
Community-Informed AI Models for Police Accountability
Proposes and illustrates a community-informed, multi-perspective approach to developing AI for analyzing LAPD body-worn camera footage of traffic stops.