MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
Table 3: Experimental results for accuracy on our MathQA and AQuA test sets
['Model', 'MathQA', 'AQuA']
The base model is referred to as “Seq2prog,” while our model with categorization is “Seq2prog + cat.” For accuracy, the performance was measured in terms of how well the model would perform on an actual math test. The gain is relatively small because the current model only uses categorization decisions as hard constraints at decoding time. Moreover, the problem categorization might be noisy due to our use of only one mathematical interpretation for each domain-specific n-gram. For example, the presence of the words “square” or “cube” in the text of a math word problem indicate that the word problem is related to the geometry domain, but these unigrams can also refer to an exponential operation (n2 or n3).