82 citations · 141 across the 10 of their papers we have counts for
7 papers · 1 filter
Hierarchical Aspect-guided Explanation Generation for Explainable Recommendation
Yidan Hu, Yong Liu, Chunyan Miao +2
Explainable recommendation systems provide explanations for recommendation results to improve their transparency and persuasiveness. The existing explainable recommendation methods…
Geometry-Entangled Visual Semantic Transformer for Image Captioning
Ling Cheng, Wei Wei, Feida Zhu +2
Recent advancements of image captioning have featured Visual-Semantic Fusion or Geometry-Aid attention refinement. However, those fusion-based models, they are still criticized for…
A Survey on Reinforcement Learning for Recommender Systems
Yuanguo Lin, Yong Liu, Fan Lin +5
Recommender systems have been widely applied in different real-life scenarios to help us find useful information. In particular, Reinforcement Learning (RL) based recommender syste…
SelfCF: A Simple Framework for Self-supervised Collaborative Filtering
Xin Zhou, Aixin Sun, Yong Liu +2
Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions. Existing CF-based methods commonly adopt nega…
Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems
Yinan Zhang, Boyang Li, Yong Liu +2
Proper initialization is crucial to the optimization and the generalization of neural networks. However, most existing neural recommendation systems initialize the user and item em…
KECRS: Towards Knowledge-Enriched Conversational Recommendation System
Tong Zhang, Yong Liu, Peixiang Zhong +3
The chit-chat-based conversational recommendation systems (CRS) provide item recommendations to users through natural language interactions. To better understand user's intentions,…