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Conversational question answering systems often rely on semantic parsing to enable interactive information retrieval, which involves the generation of structured database queries from a natural language input.
Sequence to sequence learning with neural networks
Sutskever, I., Vinyals, O., and Le, Q. V. (2014) · 2014
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Saha, A., Pahuja, V., Khapra, M. M., Sankaranarayanan, K., and Chandar, S. (2018) · 2018
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Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., and Sutskever, I. (2019) · 2019
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Editing-based SQL query generation for cross-domain context-dependent questions
Zhang, R., Yu, T., Er, H., Shim, S., Xue, E., Lin, X. V., Shi, T., Xiong, C., Socher, R., and Radev, D. (2019) · 2019
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Context dependent semantic parsing: A survey
Li, Z., Qu, L., and Haffari, G. (2020) · 2020
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Wang, B., Shin, R., Liu, X., Polozov, O., and Richardson, M. (2020) · 2020
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Aliannejadi, M., Azzopardi, L., Zamani, H., Kanoulas, E., Thomas, P., and Craswell, N. (2021) · 2021
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Gu, Y., Kase, S., Vanni, M., Sadler, B., Liang, P., Yan, X., and Su, Y. (2021) · 2021
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Conversational question answering over knowledge graphs with transformer and graph attention networks
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Liu, Q., Chen, B., Guo, J., Lou, J.-G., Zhou, B., and Zhang, D. (2021) · 2021
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Semantic parsing for conversational question answering over knowledge graphs
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