Domain Adaptation for Semantic Parsing
Table 4: The results of the ablation study, where we report the EM rate of intermediate sketch (Sketch), logical form with oracle sketch (LForacle), and the final logical form (LF). DAMP−dis is the main model without the domain discrimination component and DAMP−att is without the domain relevance attention (conventional attention only).
['Model', 'Sketch', 'LForacle', 'LF']
We perform an ablation study by taking recipes as the target domain. Despite EM of the final logical form, we also introduce EM of the obtained sketch and EM of the logical form with oracle sketch as evaluation metrics. And the main improvement comes in the coarse stage, showing that our two mechanisms can well leverage domain invariant features across multiple domains. Compared to DAMP−att, DAMP−dis performs better, specifically with about 2.8% improvement in the fine stage (LForacle). This indicates our domain relevance component is more beneficial for domain adaptation, especially for the target domain transfer in the fine stage.