Papers by John R. Woodward

3 papers
A Review of Cross-Domain Text-to-SQL Models (2020.aacl-srw)

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Challenge: WikiSQL and Spider are cross-domain text-to-SQl datasets that have attracted much attention from the research community.
Approach: They propose to divide top models into two paradigms and evaluate their models for schema linking, pretrained word embeddings, reasoning assistance modules.
Outcome: The proposed models have over 90% execution accuracy, the authors show . the proposed models are more complex and more complex than the proposed ones .
Towards Robustness of Text-to-SQL Models against Synonym Substitution (2021.acl-long)

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Challenge: Existing text-to-SQL models rely on lexical matching between words in NL questions and tokens in table schemas, which may break the schema linking mechanism.
Approach: They propose a human-curated dataset for text-to-SQL translation . they replace schema-related words with manually selected synonyms .
Outcome: The proposed model outperforms its counterparts without the defense.
Natural SQL: Making SQL Easier to Infer from Natural Language Specifications (2021.findings-emnlp)

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Challenge: Existing models that do not support executable SQL generation can generate executable queries.
Approach: They propose an SQL intermediate representation called Natural SQL (NatSQL) they propose to preserve the core functionalities of SQL while simplifying the queries .
Outcome: The proposed model outperforms existing models on a text-to-SQL benchmark . it significantly improves the performance of previous models on the same dataset .

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