Contrastive learning, a form of Self-Supervised Learning (SSL), typically consists of an
alignment term and a regularization term. The alignment term minimizes the distance …

Continual learning (CL) aims to empower machine learning models to learn continually from
new data, while building upon previously acquired knowledge without forgetting. As …

Searching on bipartite graphs serves as a fundamental task for various real-world
applications, such as recommendation systems, database retrieval, and document querying …

Recent studies highlight the potential of large language models (LLMs) to enhance content
integration in recommender systems by leveraging their semantic understanding …

Job-market mobility prediction plays a crucial role in optimizing human capital usage for
both employees and employers. Most conventional methods primarily focus on learning …

Understanding customer behavior is crucial for improving service quality in large-scale E-
commerce. This paper proposes C-STAR, a new framework that learns compact …