Coding Textual Inputs Boosts the Accuracy of Neural Networks

Abdul Rafae Khan, Jia Xu 0004, Weiwei Sun 0007. Coding Textual Inputs Boosts the Accuracy of Neural Networks. In Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu, editors, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16-20, 2020. pages 1350-1360, Association for Computational Linguistics, 2020. [doi]

@inproceedings{KhanXS20,
  title = {Coding Textual Inputs Boosts the Accuracy of Neural Networks},
  author = {Abdul Rafae Khan and Jia Xu 0004 and Weiwei Sun 0007},
  year = {2020},
  url = {https://www.aclweb.org/anthology/2020.emnlp-main.104/},
  researchr = {https://researchr.org/publication/KhanXS20},
  cites = {0},
  citedby = {0},
  pages = {1350-1360},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16-20, 2020},
  editor = {Bonnie Webber and Trevor Cohn and Yulan He and Yang Liu},
  publisher = {Association for Computational Linguistics},
  isbn = {978-1-952148-60-6},
}