research
∙
05/22/2023
Iterative Forward Tuning Boosts In-context Learning in Language Models
Large language models (LLMs) have exhibited an emergent in-context learn...
share
research
∙
01/31/2023
Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning
Table-based reasoning has shown remarkable progress in combining deep mo...
research
∙
10/23/2022
Towards Generalizable and Robust Text-to-SQL Parsing
Text-to-SQL parsing tackles the problem of mapping natural language ques...
research
∙
10/21/2022
STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing
In this paper, we propose a novel SQL guided pre-training framework STAR...
research
∙
09/15/2022
Graph-to-Text Generation with Dynamic Structure Pruning
Most graph-to-text works are built on the encoder-decoder framework with...
research
∙
09/14/2022
SUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers
This paper aims to improve the performance of text-to-SQL parsing by exp...
research
∙
08/29/2022
A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions
Text-to-SQL parsing is an essential and challenging task. The goal of te...
research
∙
06/28/2022
Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing
The importance of building text-to-SQL parsers which can be applied to n...
research
∙
03/07/2021
Improving Text-to-SQL with Schema Dependency Learning
Text-to-SQL aims to map natural language questions to SQL queries. The s...
research
∙
01/05/2021
Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing
Semantic parsing has long been a fundamental problem in natural language...
research
∙
05/12/2020
Dynamic Memory Induction Networks for Few-Shot Text Classification
This paper proposes Dynamic Memory Induction Networks (DMIN) for few-sho...
research
∙
02/27/2019
