Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem
Table 4: Ablation study of Graph2Tree on the semantic parsing (JOBS and GEO) & math word problem (MAWAPS). We employ exact match accuracy for SP and solution accuracy for MWP.
['[BOLD] Methods', '[BOLD] JOBS', '[BOLD] GEO', '[BOLD] MAWAPS']
Ablation study. We observe that two design components, the separated attention and constituency tree, are critical to our overall performance. Additionally, the initial node embedding with BiLSTM is also useful in our design. Ablation study. Attention mechanism and constituency structure both play significant roles for Graph2tree to achieve high performance in MWP solving, which is consistent with our observation in the semantic parsing task.