NumNet: Machine Reading Comprehension with Numerical Reasoning

Code

• github.com/ranqiu92/NumNet
  OfficialIn paperpytorch★ 0
• github.com/wenhuchen/gnn-tabfact
  pytorch★ 0

Abstract

Numerical reasoning, such as addition, subtraction, sorting and counting is a critical skill in human's reading comprehension, which has not been well considered in existing machine reading comprehension (MRC) systems. To address this issue, we propose a numerical MRC model named as NumNet, which utilizes a numerically-aware graph neural network to consider the comparing information and performs numerical reasoning over numbers in the question and passage. Our system achieves an EM-score of 64.56% on the DROP dataset, outperforming all existing machine reading comprehension models by considering the numerical relations among numbers.

Tasks

Benchmark Results

Reproductions