2 citations · 2 across the 4 of their papers we have counts for
4 papers
IF-GEO: Conflict-Aware Instruction Fusion for Multi-Query Generative Engine Optimization
Heyang Zhou, JiaJia Chen, Xiaolu Chen +3
As Generative Engines revolutionize information retrieval by synthesizing direct answers from retrieved sources, ensuring source visibility becomes a significant challenge. Improvi…
MindRec: A Diffusion-driven Coarse-to-Fine Paradigm for Generative Recommendation
Mengyao Gao, Chongming Gao, Haoyan Liu +5
Recent advancements in large language model-based recommendation systems often represent items as text or semantic IDs and generate recommendations in an auto-regressive manner. Ho…
Position-aware Graph Transformer for Recommendation
Jiajia Chen, Jiancan Wu, Jiawei Chen +3
Collaborative recommendation fundamentally involves learning high-quality user and item representations from interaction data. Recently, graph convolution networks (GCNs) have adva…
How Graph Convolutions Amplify Popularity Bias for Recommendation?
Jiajia Chen, Jiancan Wu, Jiawei Chen +3
Graph convolutional networks (GCNs) have become prevalent in recommender system (RS) due to their superiority in modeling collaborative patterns. Although improving the overall acc…