Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
Multimodal Large Language Models (MLLMs) are known to hallucinate, which limits their practical applications. Recent works have attempted to apply Direct Preference Optimization (DPO) to enhance the performance of MLLMs, but have shown inconsistent improvements in mitigating hallucinations. To addre…