With the rapid development of large language models (LLMs) and their integration into large
multimodal models (LMMs), there has been impressive progress in zero-shot completion of …

Visual Anomaly Detection (VAD) endeavors to pinpoint deviations from the concept of
normality in visual data, widely applied across diverse domains, eg, industrial defect …

Large Language Models (LLMs) have rapidly become important tools in Biomedical and
Health Informatics (BHI), enabling new ways to analyze data, treat patients, and conduct …

This paper does not present a novel method. Instead, it delves into an essential, yet must-
know baseline in light of the latest advancements in Generative Artificial Intelligence …

Recent research has offered insights into the extraordinary capabilities of Large Multimodal
Models (LMMs) in various general vision and language tasks. There is growing interest in …

State-of-the-art Large Multi-Modal Models (LMMs) have demonstrated exceptional
capabilities in vision-language tasks. Despite their advanced functionalities, the …

In machine learning, generalization against distribution shifts--where deployment conditions
diverge from the training scenarios--is crucial, particularly in fields like climate modeling …

Understanding the reasoning capabilities of Multimodal Large Language Models (MLLMs) is
an important area of research. In this study, we introduce a dynamic benchmark …

Anomaly detection (AD) aims to identify defective images and localize their defects (if any).
Ideally AD models should be able to detect defects over many image classes; without relying …

This paper explores the potential of Large Language Models (LLMs) in zero-shot anomaly
detection for safe visual navigation. With the assistance of the state-of-the-art real-time open …