Relational Gating for ''What If'' Reasoning
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Main Track. Pages 4015-4022.
https://doi.org/10.24963/ijcai.2021/553
Keywords
- Natural Language Processing: Question Answering
Abstract
This paper addresses the challenge of learning to do procedural reasoning over text to answer "What if..." questions. We propose a novel relational gating network that learns to filter the key entities and relationships and learns contextual and cross representations of both procedure and question for finding the answer. Our relational gating network contains an entity gating module, relation gating module, and contextual interaction module. These modules help in solving the "What if..." reasoning problem. We show that modeling pairwise relationships helps to capture higher-order relations and find the line of reasoning for causes and effects in the procedural descriptions. Our proposed approach achieves the state-of-the-art results on the WIQA dataset.
@inproceedings{ijcai2021p553,
title = {Relational Gating for ''What If'' Reasoning},
author = {Zheng, Chen and Kordjamshidi, Parisa},
booktitle = {Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, {IJCAI-21}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Prof. Zhi-Hua Zhou},
pages = {4015--4022},
year = {2021},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2021/553},
url = {https://doi.org/10.24963/ijcai.2021/553},
}
TY - CPAPER TI - Relational Gating for ''What If'' Reasoning AU - Zheng, Chen AU - Kordjamshidi, Parisa T2 - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2021 SP - 4015 EP - 4022 DO - 10.24963/ijcai.2021/553 UR - https://doi.org/10.24963/ijcai.2021/553 ER -Copied
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