Publisher
Springer International Publishing
Reference23 articles.
1. Barbieri, F., Camacho-Collados, J., Espinosa Anke, L., Neves, L.: TweetEval: Unified benchmark and comparative evaluation for tweet classification. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 1644–1650. Association for Computational Linguistics, Online (2020). https://doi.org/10.18653/v1/2020.findings-emnlp.148. https://www.aclweb.org/anthology/2020.findings-emnlp.148
2. Cer, D., et al.: Universal sentence encoder for English. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 169–174. Association for Computational Linguistics (2018). https://doi.org/10.18653/v1/D18-2029. https://www.aclweb.org/anthology/D18-2029
3. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);C Cornelis,2010
4. 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, vol. 1 (Long and Short Papers), pp. 4171–4186 (2019)
5. Duppada, V., Jain, R., Hiray, S.: SeerNet at SemEval-2018 task 1: domain adaptation for affect in tweets. In: Proceedings of The 12th International Workshop on Semantic Evaluation, pp. 18–23. Association for Computational Linguistics, New Orleans (2018). https://doi.org/10.18653/v1/S18-1002. https://www.aclweb.org/anthology/S18-1002
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献