Research map / Graph learning / Knowledge and temporal graphs
Training-free Counterfactual Explanation for Temporal Graph Model Inference
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- CoDy: Counterfactual Explainers for Dynamic Graphs (ICML 2025 · similarity 0.93)
- ST-TGExplainer: Disentangling Stability and Transition Patterns for Temporal GNN Interpretability (ICML 2026 · similarity 0.92)
- Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs (NeurIPS 2024 · similarity 0.88)
- Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks (ICLR 2024 · similarity 0.87)
- Explaining Graph Neural Networks via Structure-aware Interaction Index (ICML 2024 · similarity 0.87)
- Temporal-Aware Evaluation and Learning for Temporal Graph Neural Networks (AAAI 2025 · similarity 0.87)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
