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Learning Cross-Database Transfer of Text-queries for Adapting Text-to-SQL Parsers
Abhijeet Awasthi · Ashutosh Sathe · Sunita Sarawagi

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in Transfer Learning for Natural Language Processing »
Event URL: https://openreview.net/forum?id=pW9Z68lv_JX »

Modern Text-to-SQL semantic parsers struggle when tested on database schemas unseen during the train time. Further, model adaptation to a new database is challenging owing to zero availability of text queries for the target database until the initial deployment of the parser in the real world. We present ReFill, a framework for transferring text queries from existing databases to a target database. ReFill retrieves diverse existing text queries and masks their source-schema tokens, followed by editing and refilling with target-schema tokens for transferring text queries to the target schema. We show that this process leads to significantly more diverse text than achievable by using an SQL-to-Text generation model trained to directly translate SQL queries into natural text. Experiments across multiple relational databases establish that finetuning a semantic parser on the text synthesized by ReFill offers consistent performance gains over prior data-augmentation methods.

Author Information

Abhijeet Awasthi (IIT Bombay)
Ashutosh Sathe (Indian Institute of Technology Bombay, Indian Institute of Technology, Bombay)
Sunita Sarawagi (IIT Bombay)

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