1. Agarwal, C., Queen, O., Lakkaraju, H., Zitnik, M.: Evaluating explainability for graph neural networks. Sci. Data 10(1), 1–18 (2023)
2. Amara, K., et al.: GraphFramEx: towards systematic evaluation of explainability methods for graph neural networks. In: NeurIPS GLFrontiers Workshop (2022)
3. Bacciu, D., Errica, F., Micheli, A., Podda, M.: A gentle introduction to deep learning for graphs. Neural Netw. 129, 203–221 (2020). https://doi.org/10.1016/j.neunet.2020.06.006
4. Gunning, D., Aha, D.: DARPA’s explainable artificial intelligence (XAI) program. AI Mag. 40(2), 44–58 (2019)
5. Kakkad, J., Jannu, J., Sharma, K., Aggarwal, C., Medya, S.: A survey on explainability of graph neural networks, pp. 1–29 (2023). arXiv:2306.01958