1. Zhang, J.N., Shi, X.J., King, I., Yeung, D.Y.: Dynamic key-value memory networks for knowledge tracing. In: Proceedings of the International Conference on World Wide (2017). https://arxiv.org/abs/1611.08108
2. Ghosh, A., Heffernan, N., Lan, A.S.: Context-aware attentive knowledge tracing. In: Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining USB Stick (KDD 2020), pp. 2330–2339 (2020)
3. Piech, C., et al.: Deep knowledge tracing. In: Proceedings of the Conference on Advances in Neural Information Processing Systems, pp. 505–513 (2015). https://arxiv.org/abs/1506.05908
4. Hu, Y.F., Qiao, X., Luo, X., Peng, C.: Diversified semantic attention model for fine-grained entity typing. IEEE Access 9, 2251–2265 (2020)
5. Grefenstette, E., Hermann, K.M., Suleyman, M., Blunsom, P.: Learning to transduce with unbounded memory. In: Advances in Neural Information Processing Systems, vol. 2, pp. 1828–1836 (2015)