2026
PAS: Prelim Attention Score for Detecting Object Hallucinations in Large Vision-Language Models
CVPR 2026
Large vision-language models (LVLMs) are powerful, yet they remain unreliable due to object hallucinations. In this work, we show that in many hallucinatory predictions the LVLM effectively ignores the image and instead relies on previously generated output ("prelim") tokens to infer new objects. We