In today's competitive and fast-evolving business environment, it is a critical time for
organizations to rethink how to make talent-related decisions in a quantitative manner …

Link prediction, determining if a relation exists between two entities, is an essential task in
the analysis of heterogeneous graphs with diverse entities and relations. Despite extensive …

Group-level cognitive diagnosis, pivotal in intelligent education, aims to effectively assess
grouplevel knowledge proficiency by modeling the learning behaviors of individuals within …

Job recommendation aims to provide potential talents with suitable job descriptions (JDs)
consistent with their career trajectory, which plays an essential role in proactive talent …

Time series data pervades multiple domains, yet in real-world applications, there frequently
exists a deficiency of labels to ascertain effective representations and enable efficient …

The next basket recommendation task aims to predict the items in the user's next basket by
modeling the user's basket sequence. Existing next basket recommendations focus on …

Due to the notorious modality imbalance problem, multimodal learning (MML) leads to the
phenomenon of optimization imbalance, thus struggling to achieve satisfactory performance …

Course recommender systems can assist students in identifying suitable or appealing
courses by leveraging user interaction data, which shows previous engagements between …

In this work, we study the challenge of video Instance Segmentation (VIS), which needs to
track and segment multiple objects in videos automatically. We introduce a novel network …

Natural gas pipeline leaks pose severe risks, leading to substantial economic losses and
potential hazards to human safety. In this study, we develop an accurate model for the early …