Pretrained Foundation Models (PFMs) are regarded as the foundation for various
downstream tasks with different data modalities. A PFM (eg, BERT, ChatGPT, and GPT-4) is …

Most existing collaborative filtering techniques have focused on modeling the binary relation
of users to items by extracting from user ratings. Aside from users' ratings, their affiliated …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Recommender systems provide personalized service support to users by learning their
previous behaviors and predicting their current preferences for particular products. Artificial …

Attention mechanisms have recently boosted performance on a range of NLP tasks.
Because attention layers explicitly weight input components' representations, it is also often …

To alleviate sparsity and cold start problem of collaborative filtering based recommender
systems, researchers and engineers usually collect attributes of users and items, and design …

Online news recommender systems aim to address the information explosion of news and
make personalized recommendation for users. In general, news language is highly …

Transformer is a powerful model for text understanding. However, it is inefficient due to its
quadratic complexity to input sequence length. Although there are many methods on …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Reviews information is dominant for users to make online purchasing decisions in e-
commerces. However, the usefulness of reviews is varied. We argue that less-useful reviews …