Towards Learning to Read Like Humans

Author:

Bautista Louise Gillian,Naval Prospero

Publisher

Springer International Publishing

Reference22 articles.

1. Akbik, A., Bergmann, T., Blythe, D., Rasul, K., Schweter, S., Vollgraf, R.: FLAIR: an easy-to-use framework for state-of-the-art NLP. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations), pp. 54–59. Association for Computational Linguistics, Minneapolis, Minnesota, June 2019

2. Akbik, A., Blythe, D., Vollgraf, R.: Contextual string embeddings for sequence labeling. In: COLING 2018, 27th International Conference on Computational Linguistics, pp. 1638–1649 (2018)

3. Barrett, M., Bingel, J., Hollenstein, N., Rei, M., Søgaard, A.: Sequence classification with human attention. In: Proceedings of the 22nd Conference on Computational Natural Language Learning, pp. 302–312. Association for Computational Linguistics, Brussels, Belgium, October 2018

4. Cop, U., Dirix, N., Drieghe, D., Duyck, W.: Presenting geco: an eyetracking corpus of monolingual and bilingual sentence reading. Behav. Res. Methods 49(2), 602–615 (2017)

5. Frank, S.L., Fernandez Monsalve, I., Thompson, R.L., Vigliocco, G.: Reading time data for evaluating broad-coverage models of english sentence processing. Behav. Res. Methods 45(4), 1182–1190 (2013)

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