A Neural Framework for English-Hindi Cross-Lingual Natural Language Inference

Author:

Saikh Tanik,De Arkadipta,Bandyopadhyay Dibyanayan,Gain Baban,Ekbal Asif

Publisher

Springer International Publishing

Reference29 articles.

1. Bowman, S.R., Angeli, G., Potts, C., Manning, C.D.: A large annotated corpus for learning natural language inference. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 632–642, Lisbon, Portugal. Association for Computational Linguistics, September 2015. https://doi.org/10.18653/v1/D15-1075. https://www.aclweb.org/anthology/D15-1075

2. Chen, Q., Zhu, X., Ling, Z.H., Wei, S., Jiang, H., Inkpen, D.: Enhanced LSTM for natural language inference. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1657–1668, Vancouver, Canada. Association for Computational Linguistics, July 2017. https://doi.org/10.18653/v1/P17-1152. https://www.aclweb.org/anthology/P17-1152

3. Conneau, A., et al.: XNLI: evaluating cross-lingual sentence representations. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, pp. 2475–2485. Association for Computational Linguistics, October–November 2018. https://doi.org/10.18653/v1/D18-1269. https://www.aclweb.org/anthology/D18-1269

4. Dagan, I., Glickman, O., Magnini, B.: The PASCAL Recognising Textual Entailment Challenge. In: Quiñonero-Candela, J., Dagan, I., Magnini, B., d’Alché-Buc, F. (eds.) MLCW 2005. LNCS (LNAI), vol. 3944, pp. 177–190. Springer, Heidelberg (2006). https://doi.org/10.1007/11736790_9

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, Minnesota, pp. 4171–4186. Association for Computational Linguistics, June 2019. https://doi.org/10.18653/v1/N19-1423. https://www.aclweb.org/anthology/N19-1423

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