Multi-task learning (MTL) aims at learning related tasks in a unified model to achieve mutual
improvement among tasks considering their shared knowledge. It is an important topic in …

Fake news spread widely on social media in various domains, which lead to real-world
threats in many aspects like politics, disasters, and finance. Most existing approaches focus …

The wide spread of fake news is increasingly threatening both individuals and society. Great
efforts have been made for automatic fake news detection on a single domain (eg, politics) …

Multi-task learning has been widely applied in computational vision, natural language
processing and other fields, which has achieved well performance. In recent years, a lot of …

In most real-world large-scale online applications (eg, e-commerce or finance), customer
acquisition is usually a multi-step conversion process of audiences. For example, an …

The spread of fake news across several fields has had serious negative impacts on the
public and society. Existing studies have shown that the use of multi-domain labels can …

Scaling models to large sizes to improve performance has led a trend in deep learning, and
sparsely activated Mixture-of-Expert (MoE) is a promising architecture to scale models …

Data matching-which decides whether two data elements (eg, string, tuple, column, or
knowledge graph entity) are the" same"(aka a match)-is a key concept in data integration …

Within online platforms, it is critical to capture the dynamic user preference from the
sequential interaction behaviors for making accurate recommendation over time. Recently …

Multi-task learning (MTL) has gained significant popularity in recommender systems as it
enables the simultaneous optimization of multiple objectives. A key challenge in MTL is …