As its availability and generality in online services, implicit feedback is more commonly used
in recommender systems. However, implicit feedback usually presents noisy samples in real …

Collaborative Filtering~(CF) typically suffers from the significant challenge of popularity bias
due to the uneven distribution of items in real-world datasets. This bias leads to a significant …

Traditional recommendation systems focus on maximizing user satisfaction by suggesting
their favorite items. This user-centric approach may lead to unfair exposure distribution …

Multimedia recommendation, which incorporates various modalities (eg, images, texts, etc.)
into user or item representation to improve recommendation quality, has received …

Learning user preferences from implicit feedback is one of the core challenges in
recommendation. The difficulty lies in the potential noise within implicit feedback. Therefore …

Intelligent education stands as a prominent application of machine learning. Within this
domain, cognitive diagnosis (CD) is a key research focus that aims to diagnose students' …