Syntactic and Semantic Uniformity for Semantic Parsing and Task-Oriented Dialogue Systems (2022.findings-emnlp)
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| Challenge: | Existing approaches to model natural language use pre-trained language models, but little attention has been paid to the representation of machine-readable formats. |
| Approach: | They propose a data representation framework for semantic parsing and task-oriented dialogue systems . they define a meta grammar for syntactically uniform representations and translate semantically equivalent functions into a uniform vocabulary. |
| Outcome: | The proposed representation improves accuracy and allows for transfer learning across datasets. |
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