Large language models (LLMs) are increasingly used to generate media, but whether their content perpetuates gender stereotypes is unknown: standard benchmarks rely on selection-based formats rather than long-form generation, and surveyed baselines for local gender associations are scarce outside the West. We collect ge...
Sharif Kazemi, Tanya Popli, N. K. R. Sehgal et al.· 0 citations
A novel framework for evaluating metanorm reasoning in Large Language Models (LLMs) along two dimensions: emotional appraisal and behavioral response, and proposes new classification tasks, namely, predicting self-regulation in violators, and other-regulation in observers.
Sunny Rai, Jin-Yi Kuang, Reyhan Jamalova et al.· 0 citations
Online hate speech is associated with harms ranging from deteriorating mental health to violence, yet how consistently platforms moderate hate, and whether enforcement is feasible at scale, remain poorly understood. We audit hate speech moderation on Twitter (now X) using 540,000 tweets annotated by trained native spea...
Manuel Tonneau, D. Thurgood, Diyi Liu et al.· arXiv.org· 2 citations
It is suggested that demographic conditioning in LLMs is not a cue-invariant category-level parameter but depends fundamentally on how identity is cued, reflecting responses to linguistic signals rather than stable demographic categories.
Manuel Tonneau, Neil K. R. Seghal, Niyati Malhotra et al.· 4 citations
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