Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models

arXiv:2402.11622v1 Announce Type: cross
Abstract: Object hallucination has been an Achilles' heel which hinders the broader applications of large vision-language models (LVLMs). Object hallucination refers to the phenomenon that the LVLMs claim non-existent objects in the image. To mitigate the object hallucinations, instruction tuning and external model-based detection methods have been proposed, which either require large-scare computational resources or depend on the detection result of external models. However, there remains an under-explored field to utilize the LVLM itself to alleviate …

abstract applications arxiv claim cs.ai cs.cl cs.cv cs.lg detection detection methods hallucination hallucinations image language language models loop objects type vision vision-language models