Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

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

Recently, large language models (LLMs)(eg, GPT-4) have demonstrated impressive general-
purpose task-solving abilities, including the potential to approach recommendation tasks …

Abstract Large Language Models (LLMs) have emerged as powerful tools in the field of
Natural Language Processing (NLP) and have recently gained significant attention in the …

The problem of data sparsity has long been a challenge in recommendation systems, and
previous studies have attempted to address this issue by incorporating side information …

In the past decades, recommender systems have attracted much attention in both research
and industry communities. Existing recommendation models mainly learn the underlying …

In this paper, we present empirical studies on conversational recommendation tasks using
representative large language models in a zero-shot setting with three primary …

Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …

With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component, providing personalized …

Sequential recommendation problems have received increasing attention in research during
the past few years, leading to the inception of a large variety of algorithmic approaches. In …