arXiv cs.CLPaper
SDARE-Bench: Evaluating Large Language Models on Conversational Stigma Detection and Response in Dyadic and Group Dialogue
This is a real capability gap worth knowing about if you're deploying LLMs in customer-facing or community contexts. The result that stigma detection fails worse in group dialogue than one-on-one suggests the model's reasoning degrades under social complexity. If your application involves advice, hiring, content moderation, or any judgment call that affects reputation, run your model against this benchmark before shipping.