VCE: A zero-cost hallucination mitigation method of LVLMs via visual contrastive editing

ArXi:2604.19412v1 Announce Type: cross Large vision-language models (LVLMs) frequently suffer from Object Hallucination (OH), wherein they generate descriptions containing objects that are not actually present in the input image. This phenomenon is particularly problematic in real-world applications such as medical imaging and autonomous driving, where accuracy is critical. Recent studies suggest that the hallucination problem may stem from language priors: biases learned during pre