The emergence of Pre-trained Language Models (PLMs) has achieved tremendous success
in the field of Natural Language Processing (NLP) by learning universal representations on …

The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …

For a long time, different recommendation tasks require designing task-specific architectures
and training objectives. As a result, it is hard to transfer the knowledge and representations …

Recommendation systems have witnessed significant advancements and have been widely
used over the past decades. However, most traditional recommendation methods are task …

Large language models (LLMs) have demonstrated their significant potential to be applied
for addressing various application tasks. However, traditional recommender systems …

Industrial recommender systems have been growing increasingly complex, may
involve\emph {diverse domains} such as e-commerce products and user-generated …

Providing user-understandable explanations to justify recommendations could help users
better understand the recommended items, increase the system's ease of use, and gain …

By providing explanations for users and system designers to facilitate better understanding
and decision making, explainable recommendation has been an important research …

Structural data well exists in Web applications, such as social networks in social media,
citation networks in academic websites, and threads data in online forums. Due to the …

Recent years have witnessed the wide adoption of large language models (LLM) in different
fields, especially natural language processing and computer vision. Such a trend can also …