1 code implementation • 4 Oct 2022 • Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li
We use the model to develop a classification scheme which suppresses the impact of noise while preserving semantic cues.
1 code implementation • 2 Sep 2021 • Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim
Over the last few years, there are a growing number of datasets and deep learning-based methods proposed for effectively solving MWPs.
Ranked #8 on Math Word Problem Solving on Math23K
1 code implementation • AAAI 2019 • Lei Wang, Dongxiang Zhang, Jipeng Zhang, Xing Xu, Lianli Gao, Bing Tian Dai, Heng Tao Shen
Then, we design a recursive neural network to encode the quantity with Bi-LSTM and self attention, and infer the unknown operator nodes in a bottom-up manner.
1 code implementation • ACL 2019 • Jierui Li, Lei Wang, Jipeng Zhang, Yan Wang, Bing Tian Dai, Dongxiang Zhang
Several deep learning models have been proposed for solving math word problems (MWPs) automatically.
Ranked #13 on Math Word Problem Solving on Math23K
no code implementations • 22 Aug 2018 • Dongxiang Zhang, Lei Wang, Luming Zhang, Bing Tian Dai, Heng Tao Shen
Solving mathematical word problems (MWPs) automatically is challenging, primarily due to the semantic gap between human-readable words and machine-understandable logics.