SParC

@InProceedings{Yu&al.19, title = {SParC: Cross-Domain Semantic Parsing in Context}, author = {Tao Yu and Rui Zhang and Michihiro Yasunaga and Yi Chern Tan and Xi Victoria Lin and Suyi Li and Heyang Er, Irene Li and Bo Pang and Tao Chen and Emily Ji and Shreya Dixit and David Proctor and Sungrok Shim and Jonathan Kraft,

Papers using SParC (10)

Rose-SQL: Role-State Evolution Guided Structured Reasoning for Multi-Turn Text-to-SQL2026Track-SQL: Enhancing Generative Language Models with Dual-Extractive Modules for Schema and Context Tracking in Multi-turn Text-to-SQL2026MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Training2025IGSQL: Database Schema Interaction Graph Based Neural Model for Context-Dependent Text-to-SQL Generation2020 · 43 citesHIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsing2022 · 32 citesDecoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL2021 · 20 citesSTAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing2022 · 1 citesCoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editions2024 · 1 citesTowards Generalizable and Robust Text-to-SQL Parsing2022MIGA: A Unified Multi-task Generation Framework for Conversational Text-to-SQL2022