The study of time series is crucial for understanding trends and anomalies over time,
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …

The recommendation system is an effective approach to alleviate the information overload
caused by the popularization of the Internet. Existing recommendation methods often use …

Recent advancements in generative recommendation systems, particularly in the realm of
sequential recommendation tasks, have shown promise in enhancing generalization to new …

Generative information retrieval (Gen-IR) is a fast-growing interdisciplinary research area
that investigates how to leverage advances in generative Artificial Intelligence (AI) to …

Recommender systems remain an essential topic due to its wide application in various
domains and the business potential behind them. With the rise of deep learning, common …

While traditional recommendation techniques have made significant strides in the past
decades, they still suffer from limited generalization performance caused by factors like …

Recovering user preferences from user-item interaction matrices is a key challenge in
recommender systems. While diffusion models can sample and reconstruct preferences from …