1. Abdelali, A., Darwish, K., Durrani, N., Mubarak, H., 2016. Farasa: A fast and furious segmenter for Arabic, in: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, Association for Computational Linguistics, San Diego, California, pp. 11-16. URL: https://www.aclweb.org/anthology/N16-3003, doi: 10.18653/vl/N16-3003.
2. Alikaniotis, D., Yannakoudakis, H., Rei, M., 2016. Automatic text scoring using neural networks. arXiv preprint arXiv:1606.04289.
3. Antoun, W., Baly, R, Hajj, H., 2020. AraBERT: Transformer-based model for Arabic language understanding, in: Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection, European Language Resource Association, Marseille, France, pp. 9-15. URL: https://www.aclweb.org/anthology/2020.osact-1.2.
4. Dong, F, Zhang, Y, Yang, J., 2017. Attention-based recurrent convolutional neural network for automatic essay scoring, in: Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), pp. 153-162.
5. Dzikovska, M“ Nielsen, R“ Brew, C, Leacock, C, Giampiccolo, D“ Bentivogli, L“ Clark, P., Dagan, I., Dang, H.T., 2013. SemEval-2013 task 7: The joint student response analysis and 8th recognizing textual entailment challenge, in: Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), Association for Computational Linguistics, Atlanta, Georgia, USA. pp. 263-274. URL: https://www.aclweb.org/anthology/S13-2045.