一作ACL 2026Poster· Natural Language Processing
Modeling Annotator Disagreement with Demographic-Aware Experts and Synthetic Perspectives
Yinuo Xu · Veronica Derricks · Allison Earl · David Jurgens
摘要
We present an approach to modeling annotator disagreement in subjective NLP tasks through both architectural and data-centric innovations. Our model, DEM-MoE (Demographic-Aware Mixture of Experts), routes inputs to expert subnetworks based on annotator demographics, enabling it to better represen...