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cs.CV2026
When Visuals Aren't the Problem: Evaluating Vision-Language Models on Misleading Data Visualizations
Harsh Nishant Lalai, Raj Sanjay Shah, Hanspeter Pfister +2
Visualizations help communicate data insights, but deceptive data representations can distort their interpretation and propagate misinformation. While recent Vision Language Models…
cs.CV2026
Bias at the End of the Score
Salma Abdel Magid, Grace Guo, Esin Tureci +4
Reward models (RMs) are inherently non-neutral value functions designed and trained to encode specific objectives, such as human preferences or text-image alignment. RMs have becom…
cs.CV2024
Is What You Ask For What You Get? Investigating Concept Associations in Text-to-Image Models
Salma Abdel Magid, Weiwei Pan, Simon Warchol +4
Text-to-image (T2I) models are increasingly used in impactful real-life applications. As such, there is a growing need to audit these models to ensure that they generate desirable,…