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Found 5 papers, 2 papers with code
Inconsistency Matters: A Knowledge-guided Dual-inconsistency Network for Multi-modal Rumor Detection
Rumor spreaders are increasingly utilizing multimedia content to attract the attention and trust of news consumers.
A Differential Geometric View and Explainability of GNN on Evolving Graphs
Graphs are ubiquitous in social networks and biochemistry, where Graph Neural Networks (GNN) are the state-of-the-art models for prediction.
Inconsistent Matters: A Knowledge-guided Dual-consistency Network for Multi-modal Rumor Detection
Rumor spreaders are increasingly utilizing multimedia content to attract the attention and trust of news consumers.
Multi-objective Explanations of GNN Predictions
We design a user study to investigate such joint effects and use the findings to design a multi-objective optimization (MOO) algorithm to find Pareto optimal explanations that are well-balanced in simulatability and counterfactual.
Explaining GNN over Evolving Graphs using Information Flow
We define the problem of explaining evolving GNN predictions and propose an axiomatic attribution method to uniquely decompose the change in a prediction to paths on computation graphs.
