Automatically Solving Elementary Science Questions: A Survey
Author:
Affiliation:
1. Computer Science and Engineering Department, Visvesvaraya National Institute of Technology, Nagpur, Maharashtra, India
2. Computer Science and Engineering Department, Indian Institute of Technology, Delhi, India
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/02564602.2022.2048716
Reference81 articles.
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2. S. Min, D. Chen, H. Hajishirzi, and L. Zettlemoyer, “A discrete hard em approach for weakly supervised question answering,” in 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Association for Computational Linguistics, 2020, pp. 2851–2864.
3. K. Nishida, K. Nishida, M. Nagata, A. Otsuka, I. Saito, H. Asano, and J. Tomita, “Answering while summarizing: Multi-task learning for multi-hop qa with evidence extraction,” in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, pp. 2335–2345.
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