Abstract Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of
machine learning systems. For instance, in autonomous driving, we would like the driving …

Detecting out-of-distribution (OOD) samples is crucial for ensuring the safety of machine
learning systems and has shaped the field of OOD detection. Meanwhile, several other …

Large language models (LLMs) and vision-language models (VLMs) have demonstrated
remarkable performance across a wide range of tasks and domains. Despite this promise …

Context.—Generative artificial intelligence (GAI) is a promising new technology with the
potential to transform communication and workflows in health care and pathology. Although …

Detecting anomalies or out-of-distribution (OOD) samples is critical for maintaining the
reliability and trustworthiness of machine learning systems. Recently, Large Language …

Large multimodal models (LMMs) have demonstrated impressive capabilities in
understanding various types of image, including text-rich images. Most existing text-rich …

With the continuous advancement of vision language models (VLMs) technology,
remarkable research achievements have emerged in the dermatology field, the fourth most …

Context.—Generative artificial intelligence (AI) has emerged as a transformative force in
various fields, including anatomic pathology, where it offers the potential to significantly …

With the recent emergence of foundation models trained on internet-scale data and
demonstrating remarkable generalization capabilities, such foundation models have …

Accelerating research on Large Multimodal Models (LMMs) in non-English languages is
crucial for enhancing user experiences across broader populations. In this paper, we …