Vision systems that see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …

With the widespread application of the Transformer architecture in various modalities,
including vision, the technology of large language models is evolving from a single modality …

The emergence of large language models (LLMs) has marked a significant breakthrough in
natural language processing (NLP), fueling a paradigm shift in information acquisition …

Hallucinations is a big shadow hanging over the rapidly evolving multimodal large language
models (MLLMs), referring to that the generated text is inconsistent with the image content …

Multimodal Large Language Models (MLLMs) have tremendous potential to improve the
accuracy, availability, and cost-effectiveness of healthcare by providing automated solutions …

Recent development of Large Vision-Language Models (LVLMs) has attracted growing
attention within the AI landscape for its practical implementation potential. However,`` …

Despite significant strides in multimodal tasks, Multimodal Large Language Models (MLLMs)
are plagued by the critical issue of hallucination. The reliable detection of such …

Abstract Recent Large Vision Language Models (LVLMs) present remarkable zero-shot
conversational and reasoning capabilities given multimodal queries. Nevertheless, they …

The remarkable advancements in Multimodal Large Language Models (MLLMs) have not
rendered them immune to challenges, particularly in the context of handling deceptive …

This survey presents a comprehensive analysis of the phenomenon of hallucination in
multimodal large language models (MLLMs), also known as Large Vision-Language Models …