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Current state-of-art feature-engineered and end-to-end Automated Essay Score (AES) methods are proven to be unable to detect adversarial samples, e.g.
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2016
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Y. Farag, H. Yannakoudakis, and T. Briscoe, “Neural automated essay scoring and coherence modeling for adversarially crafted input,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , vol. 1, 2018, pp. 263–271
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J. Li and E. Hovy, “A model of coherence based on distributed sentence representation,” in Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) , 2014, pp. 2039–2048
2048
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