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Beyond Predictions: A Participatory Framework for Multi-Stakeholder Decision-Making

COMBINEX: A Unified Counterfactual Explainer for Graph Neural Networks via Node Feature and Structural Perturbations

Community Membership Hiding via Gradient-based Optimization

Consistent Counterfactual Explanations via Anomaly Control and Data Coherence

FROG: Fair Removal on Graphs

Generalizability through Explainability: Countering Overfitting with Counterfactual Examples

(∇) (τ): Gradient-based and Task-Agnostic machine Unlearning

Debiasing Machine Unlearning with Counterfactual Examples

Explain the Explainer: Interpreting Model-Agnostic Counterfactual Explanations of a Deep Reinforcement Learning Agent

Natural Language Counterfactual Explanations for Graphs Using Large Language Models