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…
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Published5 h ago (Fri, 18 Sep 2026 04:00:00 GMT)
RetrievedFri, 18 Sep 2026 08:00:48 GMT via rss
ClassifiedFri, 18 Sep 2026 08:01:04 GMT by heuristic
AuthorYingjia Wan, Lin Lin, Elisa Kreiss