24 citations · 59 across the 9 of their papers we have counts for
11 papers
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…
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,…
Understanding Chinese Video and Language via Contrastive Multimodal Pre-Training
Chenyi Lei, Shixian Luo, Yong Liu +6
The pre-trained neural models have recently achieved impressive performances in understanding multimodal content. However, it is still very challenging to pre-train neural models f…
Pre-training Graph Transformer with Multimodal Side Information for Recommendation
Yong Liu, Susen Yang, Chenyi Lei +5
Side information of items, e.g., images and text description, has shown to be effective in contributing to accurate recommendations. Inspired by the recent success of pre-training…