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cs.CL2026
How Humans and LLMs Read Gender into "Gender-Neutral" Physical Descriptions
Yingjia Wan, Lin Lin, Elisa Kreiss
When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., "she", "his") in favor of seemingl…
cs.CL2025
Measuring Bias or Measuring the Task: Understanding the Brittle Nature of LLM Gender Biases
Bufan Gao, Elisa Kreiss
As LLMs are increasingly applied in socially impactful settings, concerns about gender bias have prompted growing efforts both to measure and mitigate such bias. These efforts ofte…
cs.CL2025
MOSAIC: Modeling Social AI for Content Dissemination and Regulation in Multi-Agent Simulations
Genglin Liu, Vivian Le, Salman Rahman +3
We present a novel, open-source social network simulation framework, MOSAIC, where generative language agents predict user behaviors such as liking, sharing, and flagging content.…