Automatic summarization of legal case judgements, which are known to be long and
complex, has traditionally been tried via extractive summarization models. In recent years …

The rapid advancement of foundation models (FMs) across language, image, audio, and
video domains has shown remarkable capabilities in diverse tasks. However, the …

Abstract Large Language Models (LLMs) such as General Pretrained Transformer (GPT)
and Bidirectional Encoder Representations from Transformers (BERT), which use …

Retrieval augmented generation (RAG) is often used to fix hallucinations and provide up-to-
date knowledge for large language models (LLMs). However, in cases when the LLM alone …

Retrieval augmented generation (RAG) is frequently used to mitigate hallucinations and
provide up-to-date knowledge for large language models (LLMs). However, given that …

With the explosive growth of medical data and the rapid development of artificial intelligence
technology, precision medicine has emerged as a key to enhancing the quality and …

Abstract Large Language Models have demonstrated expert-level accuracy on medical
board examinations, suggesting potential for clinical decision support systems. However …

Multimodal foundation models hold significant potential for automating radiology report
generation, thereby assisting clinicians in diagnosing cardiac diseases. However, generated …

Despite the great success of Large Vision-Language Models (LVLMs), they inevitably suffer
from hallucination. As we know, both the visual encoder and the Large Language Model …

Large language models (LLMs) have shown potential in biomedical applications, leading to
efforts to fine-tune them on domain-specific data. However, the effectiveness of this …