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Found 2 papers, 1 papers with code
Disentangling the Potential Impacts of Papers into Diffusion, Conformity, and Contribution Values
In this study, we propose a novel graph neural network to Disentangle the Potential impacts of Papers into Diffusion, Conformity, and Contribution values (called DPPDCC).
H2CGL: Modeling Dynamics of Citation Network for Impact Prediction
Then, a novel graph neural network, Hierarchical and Heterogeneous Contrastive Graph Learning Model (H2CGL), is proposed to incorporate heterogeneity and dynamics of the citation network.
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