🔗 Who cites «TypeSQL: Knowledge-Based Type-Aware Neural Text-to-SQL Generation»

65 papers of our library cite it (of the 140,884 whose bibliographies we read) · 9 with a page here, the most cited first · ← the paper

1. Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL TaskTao Yu, Rui Zhang, Kai Yang, et al.2018 · 1,582 citations
2. TaBERT: Pretraining for Joint Understanding of Textual and Tabular DataPengcheng Yin, Graham Neubig, Wen-tau Yih, et al.2020 · 690 citations
3. The Natural Language Decathlon: Multitask Learning as Question AnsweringBryan McCann, Nitish Shirish Keskar, Caiming Xiong, et al.2018 · 523 citations
4. Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLsJinyang Li, Binyuan Hui, Ge Qu, et al.2023 · 419 citations
5. RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLHaoyang Li, Jing Zhang, Cuiping Li, et al.2023 · 277 citations
6. CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to DatabasesTao Yu, Rui Zhang, Heyang Er, et al.2019 · 261 citations
7. A Discrete Hard EM Approach for Weakly Supervised Question AnsweringSewon Min, Danqi Chen, Hannaneh Hajishirzi, et al.2019 · 233 citations
8. SParC: Cross-Domain Semantic Parsing in ContextTao Yu, Rui Zhang, Michihiro Yasunaga, et al.2019 · 227 citations
9. Structure-Grounded Pretraining for Text-to-SQLXiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.2021 · 166 citations

56 more papers of our library cite it; they have no page here yet.

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