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Greatest papers with code

Improving Text-to-SQL Evaluation Methodology

ACL 2018 jkkummerfeld/text2sql-data

Second, we show that the current division of data into training and test sets measures robustness to variations in the way questions are asked, but only partially tests how well systems generalize to new queries; therefore, we propose a complementary dataset split for evaluation of future work.

SQL PARSING TEXT-TO-SQL

Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing

ACL 2019 benbogin/spider-schema-gnn

Research on parsing language to SQL has largely ignored the structure of the database (DB) schema, either because the DB was very simple, or because it was observed at both training and test time.

SQL PARSING TEXT-TO-SQL

Global Reasoning over Database Structures for Text-to-SQL Parsing

IJCNLP 2019 benbogin/spider-schema-gnn-global

State-of-the-art semantic parsers rely on auto-regressive decoding, emitting one symbol at a time.

SEMANTIC PARSING SQL PARSING TEXT-TO-SQL

Learning to Synthesize Data for Semantic Parsing

12 Apr 2021berlino/tensor2struct-public

Moreover, explicitly modeling compositions using PCFG leads to a better exploration of unseen programs, thus generate more diverse data.

DOMAIN GENERALIZATION SEMANTIC PARSING SQL PARSING TEXT-TO-SQL

A Tale of Two Linkings: Dynamically Gating between Schema Linking and Structural Linking for Text-to-SQL Parsing

30 Sep 2020sanxing-chen/linking-tale

In Text-to-SQL semantic parsing, selecting the correct entities (tables and columns) for the generated SQL query is both crucial and challenging; the parser is required to connect the natural language (NL) question and the SQL query to the structured knowledge in the database.

SEMANTIC PARSING SQL PARSING TEXT-TO-SQL