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 …

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

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

Social media platforms are hubs for multimodal information exchange, encompassing text,
images, and videos, making it challenging for machines to comprehend the information or …

The" Graph pre-training and fine-tuning" paradigm has significantly improved Graph Neural
Networks (GNNs) by capturing general knowledge without manual annotations for …

Large language models (LLMs) are transforming the ways the general public accesses and
consumes information. Their influence is particularly pronounced in pivotal sectors like …

Large language models (LLMs) have demonstrated a powerful ability to answer various
queries as a general-purpose assistant. The continuous multi-modal large language models …

Recent advancements in generative AI have suggested that by taking visual prompt, GPT-4V
can demonstrate significant proficiency in image recognition task. Despite its impressive …

Sequential recommender systems (SRS) are designed to predict users' future behaviors
based on their historical interaction data. Recent research has increasingly utilized …

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 …