arxiv
PublishedSeptember 1, 2026 at 4:00 AM
Vision-Language Models Suppress Female Representations Under Ambiguous Input
Publisher summary· verbatim
arXiv:2605.31556v2 Announce Type: replace-cross Abstract: Alignment teaches vision-language models (VLMs) to avoid expressing demographic biases, and when gender is clearly visible they largely succeed. Far less is known about ambiguous inputs (a worker in full gear, a figure seen from behind), case
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivCulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning17harxivProactive Service Agents: A Unified Decision Framework, Methods, and Evaluation17harxivX-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System17harxivA Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors17hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗