Question Directed Graph Attention Network for Numerical Reasoning over Text

September 16, 2020 · Entered Twilight · 🏛 Conference on Empirical Methods in Natural Language Processing

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Repo contents: README.md, qdgat

Authors Kunlong Chen, Weidi Xu, Xingyi Cheng, Zou Xiaochuan, Yuyu Zhang, Le Song, Taifeng Wang, Yuan Qi, Wei Chu arXiv ID 2009.07448 Category cs.AI: Artificial Intelligence Citations 68 Venue Conference on Empirical Methods in Natural Language Processing Repository https://github.com/emnlp2020qdgat/QDGAT ⭐ 2 Last Checked 2 months ago

Abstract

Numerical reasoning over texts, such as addition, subtraction, sorting and counting, is a challenging machine reading comprehension task, since it requires both natural language understanding and arithmetic computation. To address this challenge, we propose a heterogeneous graph representation for the context of the passage and question needed for such reasoning, and design a question directed graph attention network to drive multi-step numerical reasoning over this context graph. The code link is at: https://github.com/emnlp2020qdgat/QDGAT