Hybrid Ranking Network for Text-to-SQL

2 code implementations • 11 Aug 2020 • Qin Lyu, Kaushik Chakrabarti, Shobhit Hathi, Souvik Kundu, Jianwen Zhang, Zheng Chen

In this paper, we study how to leverage pre-trained language models in Text-to-SQL.

Language Modelling Text-To-SQL

Open Domain Question Answering Using Web Tables

no code implementations • 10 Jan 2020 • Kaushik Chakrabarti, Zhimin Chen, Siamak Shakeri, Guihong Cao

Tables extracted from web documents can be used to directly answer many web search queries.

Open-Domain Question Answering Semantic Similarity +1

TableQnA: Answering List Intent Queries With Web Tables

no code implementations • 10 Jan 2020 • Kaushik Chakrabarti, Zhimin Chen, Siamak Shakeri, Guihong Cao, Surajit Chaudhuri

For (ii), we develop novel features to compute structure-aware match and train a machine learning model.

BIG-bench Machine Learning Word Embeddings

X-SQL: reinforce schema representation with context

no code implementations • 21 Aug 2019 • Pengcheng He, Yi Mao, Kaushik Chakrabarti, Weizhu Chen

In this work, we present X-SQL, a new network architecture for the problem of parsing natural language to SQL query.

IncSQL: Training Incremental Text-to-SQL Parsers with Non-Deterministic Oracles

no code implementations • 13 Sep 2018 • Tianze Shi, Kedar Tatwawadi, Kaushik Chakrabarti, Yi Mao, Oleksandr Polozov, Weizhu Chen

We present a sequence-to-action parsing approach for the natural language to SQL task that incrementally fills the slots of a SQL query with feasible actions from a pre-defined inventory.

Action Parsing Text-To-SQL