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 …

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 …

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 …

Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …

Recommender systems have emerged as indispensable tools for information filtering, and
the integration of knowledge graphs for auxiliary information is becoming an increasingly …

Computer Vision (CV), Natural Language Processing (NLP), and Recommender Systems
(RecSys) are three prominent AI applications that have traditionally developed …

Harnessing Large Language Models (LLMs) for recommendation is rapidly emerging, which
relies on two fundamental steps to bridge the recommendation item space and the language …

Foundation Models such as Large Language Models (LLMs) have significantly advanced
many research areas. In particular, LLMs offer significant advantages for recommender …

In modern recommender systems, there are usually comments or reviews from users that
justify their ratings for different items. Trained on such textual corpus, explainable …

Session-based recommendation aims to predict intents of anonymous users based on their
limited behaviors. Modeling user behaviors involves two distinct rationales: co-occurrence …