Reducing Hallucination in Multimodal Large Language Models through Hard Grounding Preference Supervision

Hallucination remains a major challenge in vision-language models (VLMs), particularly when linguistically plausible responses are unsupported by visual evidence. We study whether multimodal hallucination can be reduced by concentrating post-training supervision on hard grounding boundaries, where p