most citedDistance-aware Self-adaptive Graph Convolution for Fine-grained Hierarchical Recommendation

1 citations · 1 across the 1 of their papers we have counts for

collaborators
Showing cs.IRShow all

2 papers · 1 filter

cs.IR2026

Personalized Task Dependency Graphs for Mitigating Signal Erosion in Multi-Task Recommendation

Fuyuan Liu, Tiandeng Wu, Yaqun Fang +8

Optimizing multiple conversion objectives is a core challenge in industrial recommendation, often limited by signal erosion in rigid architectures. Existing Multi-Task Learning (MT…

cs.IR2025★ 1 cited

Distance-aware Self-adaptive Graph Convolution for Fine-grained Hierarchical Recommendation

Tao Huang, Yihong Chen, Wei Fan +2

Graph Convolutional Networks (GCNs) are widely used to improve recommendation accuracy and performance by effectively learning the representations of user and item nodes. However,…