Large language models (LLMs), such as GPT4 and LLaMA, are creating significant
advancements in natural language processing, due to their strong text encoding/decoding …

Recommender system is one of the most important information services on today's Internet.
Recently, graph neural networks have become the new state-of-the-art approach to …

Sequential recommendation aims to leverage users' historical behaviors to predict their next
interaction. Existing works have not yet addressed two main challenges in sequential …

With the explosive growth of online information, recommender systems play a key role to
alleviate such information overload. Due to the important application value of recommender …

Recently, graph neural network (GNN) has become the new state-of-the-art approach in
many recommendation problems, with its strong ability to handle structured data and to …

Design for manufacture and assembly (DfMA) in the architectural, engineering, and
construction (AEC) industry is attracting the attention of designers, practitioners, and …

Bundle recommendation aims to recommend a bundle of related items to users, which can
satisfy the users' various needs with one-stop convenience. Recent methods usually take …

The recommender system (RS) has been an integral toolkit of online services. They are
equipped with various deep learning techniques to model user preference based on …

Bundle recommendation aims to recommend the user a bundle of items as a whole.
Previous models capture user's preferences on both items and the association of items …

Session-based recommendation (SBR) aims at the next-item prediction with a short
behavior session. Existing solutions fail to address two main challenges: 1) user interests …