310 citations · 912 across the 25 of their papers we have counts for
7 papers · 1 filter
A Survey on Large Language Models for Recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu +9
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recomm…
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation
Kai Zhang, Hao Qian, Qi Liu +4
Recent studies in recommender systems have managed to achieve significantly improved performance by leveraging reviews for rating prediction. However, despite being extensively stu…
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction
Kai Zhang, Hao Qian, Qing Cui +5
In the Click-Through Rate (CTR) prediction scenario, user's sequential behaviors are well utilized to capture the user interest in the recent literature. However, despite being ext…
Sampling-Decomposable Generative Adversarial Recommender
Binbin Jin, Defu Lian, Zheng Liu +4
Recommendation techniques are important approaches for alleviating information overload. Being often trained on implicit user feedback, many recommenders suffer from the sparsity c…
Learning the Compositional Visual Coherence for Complementary Recommendations
Zhi Li, Bo Wu, Qi Liu +3
Complementary recommendations, which aim at providing users product suggestions that are supplementary and compatible with their obtained items, have become a hot topic in both aca…
Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach
Min Hou, Le Wu, Enhong Chen +3
In fashion recommender systems, each product usually consists of multiple semantic attributes (e.g., sleeves, collar, etc). When making cloth decisions, people usually show prefere…