Causal inference has recently garnered significant interest among recommender system
(RS) researchers due to its ability to dissect cause-and-effect relationships and its broad …

Some recent news recommendation (NR) methods introduce a Pre-trained Language Model
(PLM) to encode news representation by following the vanilla pre-train and fine-tune …

Personalized news recommendation is an essential technique for online news services.
News articles usually contain rich textual content, and accurate news modeling is important …

Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …

Personalized news recommendation is an important technology to help users obtain news
information they are interested in and alleviate information overload. In recent years, news …

Personalized news recommendation is a critical technology to improve users' online news
reading experience. The core of news recommendation is accurate matching between user's …

The most important task in personalized news recommendation is accurate matching
between candidate news and user interest. Most of existing news recommendation methods …

News recommendation aims to display news articles to users based on their personal
interest. Existing news recommendation methods rely on centralized storage of user …

User interest modeling is critical for personalized news recommendation. Existing news
recommendation methods usually learn a single user embedding for each user from their …

Accurate user interest modeling is important for news recommendation. Most existing
methods for news recommendation rely on implicit feedbacks like click for inferring user …