8 citations · 9 across the 4 of their papers we have counts for
5 papers
MLLMRec: A Preference Reasoning Paradigm with Graph Refinement for Multimodal Recommendation
Yuzhuo Dang, Xin Zhang, Zhiqiang Pan +4
Multimodal recommendation combines the user historical behaviors with the modal features of items to capture the tangible user preferences, presenting superior performance compared…
Disentangled Variational Auto-encoder Enhanced by Counterfactual Data for Debiasing Recommendation
Yupu Guo, Fei Cai, Xin Zhanga +2
Recommender system always suffers from various recommendation biases, seriously hindering its development. In this light, a series of debias methods have been proposed in the recom…
Pre-train, Interact, Fine-tune: A Novel Interaction Representation for Text Classification
Jianming Zheng, Fei Cai, Honghui Chen +1
Text representation can aid machines in understanding text. Previous work on text representation often focuses on the so-called forward implication, i.e., preceding words are taken…
Joint Neural Collaborative Filtering for Recommender Systems
Wanyu Chen, Fei Cai, Honghui Chen +1
We propose a J-NCF method for recommender systems. The J-NCF model applies a joint neural network that couples deep feature learning and deep interaction modeling with a rating mat…
Attention-based Hierarchical Neural Query Suggestion
Wanyu Chen, Fei Cai, Honghui Chen +1
Query suggestions help users of a search engine to refine their queries. Previous work on query suggestion has mainly focused on incorporating directly observable features such as…