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 …

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 …

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 …

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

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

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

Learning from feedback reduces the hallucination of multimodal large language models
(MLLMs) by aligning them with human preferences. While traditional methods rely on labor …

Instruction-following Vision Large Language Models (VLLMs) have achieved significant
progress recently on a variety of tasks. These approaches merge strong pre-trained vision …

While large vision-language models (LVLMs) have demonstrated impressive capabilities in
interpreting multi-modal contexts, they invariably suffer from object hallucinations (OH). We …