---
title: "Who cites Learning to Parse Database Queries Using…"
description: "358 papers of the Elamur Research library cite «Learning to Parse Database Queries Using Inductive Logic Programming», found in their bibliographies; the…"
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---
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# Who cites «Learning to Parse Database Queries Using Inductive Logic Programming»

358 papers of our library cite it (of the 140,884 whose bibliographies we read) · 39 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/zelle-1996-learning-parse-database-queries-using/)

1. [**Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task**Tao Yu, Rui Zhang, Kai Yang, et al.*2018 · 1,582 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/)
2. [**DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs**Dheeru Dua, Yizhong Wang, Pradeep Dasigi, et al.*2019 · 941 citations*](https://md.research.elamur.ai/free/en/papers/dua-2019-drop-reading-comprehension-benchmark-requiring/)
3. [**MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text**Matthew Richardson, Christopher J.C. Burges, Erin Renshaw*2013 · 873 citations*](https://md.research.elamur.ai/free/en/papers/richardson-2013-mctest-challenge-dataset-open-domain/)
4. [**TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 690 citations*](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/)
5. [**A simple neural network module for relational reasoning**Adam Santoro, David Raposo, David G. T. Barrett, et al.*2017 · 590 citations*](https://md.research.elamur.ai/free/en/papers/santoro-2017-simple-neural-network-module-relational/)
6. [**A Discriminative Graph-Based Parser for the Abstract Meaning Representation**Jeffrey Flanigan, Sam Thomson, Jaime Carbonell, et al.*2014 · 508 citations*](https://md.research.elamur.ai/free/en/papers/flanigan-2014-discriminative-graph-based-parser-abstract/)
7. [**MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms**Aida Amini, Saadia Gabriel, Shanchuan Lin, et al.*2019 · 500 citations*](https://md.research.elamur.ai/free/en/papers/amini-2019-mathqa-interpretable-math-word-problem/)
8. [**Semantic Parsing for Single-Relation Question Answering**Wen-tau Yih, Xiaodong He, Christopher Meek*2014 · 483 citations*](https://md.research.elamur.ai/free/en/papers/yih-2014-semantic-parsing-single-relation-question/)
9. [**Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus**Yuk Wah Wong, Raymond Mooney*2007 · 464 citations*](https://md.research.elamur.ai/free/en/papers/wong-2007-learning-synchronous-grammars-semantic-parsing/)
10. [**Show your work: Scratchpads for intermediate computation with language models***2021 · 448 citations*](https://md.research.elamur.ai/free/en/papers/al-2021-show-your-work-scratchpads-intermediate/)
11. [**Paraphrase-Driven Learning for Open Question Answering**Anthony Fader, Luke Zettlemoyer, Oren Etzioni*2013 · 438 citations*](https://md.research.elamur.ai/free/en/papers/fader-2013-paraphrase-driven-learning-open-question/)
12. [**Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs**Jinyang Li, Binyuan Hui, Ge Qu, et al.*2023 · 419 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-llm-already-serve-database-interface/)
13. [**UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models**Tianbao Xie, Chen Henry Wu, Peng Shi, et al.*2022 · 405 citations*](https://md.research.elamur.ai/free/en/papers/xie-2022-unifiedskg-unifying-multi-tasking-structured/)
14. [**Compositional Semantic Parsing on Semi-Structured Tables**Panupong Pasupat, Percy Liang*2015 · 404 citations*](https://md.research.elamur.ai/free/en/papers/pasupat-2015-compositional-semantic-parsing-semi-structured/)
15. [**Learning for Semantic Parsing with Statistical Machine Translation**Yuk Wah Wong, Raymond Mooney*2006 · 370 citations*](https://md.research.elamur.ai/free/en/papers/wong-2006-learning-semantic-parsing-statistical-machine/)
16. [**Question Answering on Freebase via Relation Extraction and Textual Evidence**Kun Xu, Siva Reddy, Yansong Feng, et al.*2016 · 357 citations*](https://md.research.elamur.ai/free/en/papers/xu-2016-question-answering-freebase-relation-extraction/)
17. [**Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars**Luke S. Zettlemoyer, Michael Collins*2012 · 345 citations*](https://md.research.elamur.ai/free/en/papers/zettlemoyer-2012-learning-map-sentences-logical-form/)
18. [**The Web as a Knowledge-Base for Answering Complex Questions**Alon Talmor, Jonathan Berant*2018 · 316 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2018-web-as-knowledge-base-answering/)
19. [**Multi-hop Reading Comprehension through Question Decomposition and Rescoring**Sewon Min, Victor Zhong, Luke Zettlemoyer, et al.*2019 · 306 citations*](https://md.research.elamur.ai/free/en/papers/min-2019-multi-hop-reading-comprehension-through/)
20. [**Lexical Generalization in CCG Grammar Induction for Semantic Parsing**Tom Kwiatkowski, Luke Zettlemoyer, Sharon Goldwater, et al.*2011 · 283 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2011-lexical-generalization-ccg-grammar-induction/)
21. [**RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL**Haoyang Li, Jing Zhang, Cuiping Li, et al.*2023 · 277 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-resdsql-decoupling-schema-linking-skeleton/)
22. [**Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing**Ben Bogin, Jonathan Berant, Matt Gardner*2019 · 272 citations*](https://md.research.elamur.ai/free/en/papers/bogin-2019-representing-schema-structure-graph-neural/)
23. [**Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing**Xi Victoria Lin, Richard Socher, Caiming Xiong*2020 · 261 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/)
24. [**CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases**Tao Yu, Rui Zhang, Heyang Er, et al.*2019 · 261 citations*](https://md.research.elamur.ai/free/en/papers/yu-2019-cosql-conversational-text-sql-challenge/)
25. [**Learning Context-Dependent Mappings from Sentences to Logical Form**Luke Zettlemoyer, Michael Collins*2009 · 246 citations*](https://md.research.elamur.ai/free/en/papers/zettlemoyer-2009-learning-context-dependent-mappings-sentences/)
26. [**RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers**Bailin Wang, Richard Shin, Xiaodong Liu, et al.*2020 · 239 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-rat-sql-relation-aware-schema/)
27. [**Broad-coverage CCG Semantic Parsing with AMR**Yoav Artzi, Kenton Lee, Luke Zettlemoyer*2015 · 228 citations*](https://md.research.elamur.ai/free/en/papers/artzi-2015-broad-coverage-ccg-semantic-parsing/)
28. [**SParC: Cross-Domain Semantic Parsing in Context**Tao Yu, Rui Zhang, Michihiro Yasunaga, et al.*2019 · 227 citations*](https://md.research.elamur.ai/free/en/papers/yu-2019-sparc-cross-domain-semantic-parsing/)
29. [**Break It Down: A Question Understanding Benchmark**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/)
30. [**LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/)
31. [**Structure-Grounded Pretraining for Text-to-SQL**Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.*2021 · 166 citations*](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/)
32. [**Binding Language Models in Symbolic Languages**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 165 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/)
33. [**Diverse Demonstrations Improve In-context Compositional Generalization**Itay Levy, Ben Bogin, Jonathan Berant*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/levy-2023-diverse-demonstrations-improve-context-compositional/)
34. [**Scaling Semantic Parsers with On-the-Fly Ontology Matching**Tom Kwiatkowski, Eunsol Choi, Yoav Artzi, et al.*2013 · 134 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2013-scaling-semantic-parsers-fly-ontology/)
35. [**LEVER: Learning to Verify Language-to-Code Generation with Execution**Ansong Ni, Srini Iyer, Dragomir Radev, et al.*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/)
36. [**Parsing English into Abstract Meaning Representation Using Syntax-Based Machine Translation**Michael Pust, Ulf Hermjakob, Kevin Knight, et al.*2015 · 109 citations*](https://md.research.elamur.ai/free/en/papers/pust-2015-parsing-english-into-abstract-meaning/)
37. [**Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds**Igor Labutov, Bishan Yang, Anusha Prakash, et al.*2018 · 17 citations*](https://md.research.elamur.ai/free/en/papers/labutov-2018-multi-relational-question-answering-narratives/)
38. [**Prompt Engineering Techniques for Context-dependent Text-to-SQL in Arabic**Saleh Almohaimeed, May Alsofyani, Saad Almohaimeed, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/almohaimeed-2025-prompt-engineering-techniques-context-dependent/)
39. [**AraSpider: Democratizing Arabic-to-SQL**Ahmed Heakl; Youssef Mohamed;, Ahmed B. Zaky*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/heakl-2024-araspider-democratizing-arabic-sql/)

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

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