Foundation models trained on large-scale dataset gain a recent surge in CV and NLP. In
contrast, development in biomedical domain lags far behind due to data scarcity. To address …

Medical vision-language models (VLMs) combine computer vision and natural language
processing to analyze visual and textual medical data. Our paper reviews recent …

As Large Language Models (LLMs) become popular, there emerged an important trend of
using multimodality to augment the LLMs' generation ability, which enables LLMs to better …

The number of Language Models (LMs) dedicated to processing scientific text is on the rise.
Keeping pace with the rapid growth of scientific LMs (SciLMs) has become a daunting task …

The rapid advancement of large-scale vision-language models has showcased remarkable
capabilities across various tasks. However, the lack of extensive and high-quality image-text …

Queries with similar information needs tend to have similar document clicks, especially in
biomedical literature search engines where queries are generally short and top documents …

The recent emergence of Medical Large Vision Language Models (Med-LVLMs) has
enhanced medical diagnosis. However, current Med-LVLMs frequently encounter factual …

Research on Multi-modal Large Language Models (MLLMs) towards the multi-image cross-
modal instruction has received increasing attention and made significant progress …

Large language models (LLMs), such as GPT series models, have received substantial
attention due to their impressive capabilities for generating and understanding human-level …

With the rise of large-scale vision-language pretraining (VLP), tremendous progress has
been achieved in handling complex multi-modal information in general domain. However …