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

Abstract In recent years, Large Language Models (LLMs) have emerged as powerful tools
for diverse natural language processing tasks. However, their potential for recommender …

Recently, sequential recommendation has been adapted to the LLM paradigm to enjoy the
power of LLMs. LLM-based methods usually formulate recommendation information into …

Hallucination is a significant barrier to the utilization of large-scale language models or
multimodal models. In this study, we collected 654 computer science papers with" …

Intent learning, which aims to learn users' intents for user understanding and item
recommendation, has become a hot research spot in recent years. However, the existing …

Sequential Recommendation (SR) task involves predicting the next item a user is likely to
interact with, given their past interactions. The SR models examine the sequence of a user's …

With the information explosion on the Web, search and recommendation are foundational
infrastructures to satisfying users' information needs. As the two sides of the same coin, both …

Recent advancements in Large Language Models (LLMs) have attracted considerable
interest among researchers to leverage these models to enhance Recommender Systems …

Recommender systems (RS) serve as a fundamental tool for navigating the vast expanse of
online information, with deep learning advancements playing an increasingly important role …

Hallucination is a significant barrier to the utilization of large-scale language models or
multimodal models. In this study, we collected 654 computer science papers with …