How Humans and LLMs Read Gender into "Gender-Neutral" Physical Descriptions.

arXiv:2609.16366v2 Announce Type: replace-cross Abstract: 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 seemingly "objective" physical