Large language models (LLM) not only have revolutionized the field of natural language
processing (NLP) but also have the potential to reshape many other fields, eg, recommender …

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

The recent surge in Large Language Models (LLMs) has garnered significant attention
across numerous fields. Fine-tuning is often required to fit general LLMs for a specific …

Large language models (LLMs) have not only revolutionized the field of natural language
processing (NLP) but also have the potential to bring a paradigm shift in many other fields …

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 …

Large Language Models (LLMs) have demonstrated remarkable capabilities and have been
extensively deployed across various domains, including recommender systems. Prior …

Federated recommendation systems employ federated learning techniques to safeguard
user privacy by transmitting model parameters instead of raw user data between user …

Sequential recommender systems (SRS) aim to predict users' subsequent choices based on
their historical interactions and have found applications in diverse fields such as e …

Large Language Model (LLM) has transformative potential in various domains, including
recommender systems (RS). There have been a handful of research that focuses on …

Nowadays, large language models (LLMs) have been integrated with conventional
recommendation models to improve recommendation performance. However, while most of …