With the rapid development of online services and web applications, recommender systems
(RS) have become increasingly indispensable for mitigating information overload and …

Recent advancements in large language models (LLMs) have transformed the field of
question answering (QA). However, evaluating LLMs in the medical field is challenging due …

Integrating large language models (LLMs) into healthcare holds great potential but faces
challenges. Pre-training LLMs from scratch for domains like medicine is resource-heavy and …

The remarkable advancements in Multimodal Large Language Models (MLLMs) have not
rendered them immune to challenges, particularly in the context of handling deceptive …

Graph Neural Networks (GNNs) have emerged as promising solutions for collaborative
filtering (CF) through the modeling of user-item interaction graphs. The nucleus of existing …

This study compared the classification performance of Gemini Pro and GPT-4V in
educational settings. Employing visual question answering (VQA) techniques, the study …

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 …

In the realm of personalized recommender systems, the challenge of adapting to evolving
user preferences and the continuous influx of new users and items is paramount …

Recently, Foundation Models (FMs), with their extensive knowledge bases and complex
architectures, have offered unique opportunities within the realm of recommender systems …