--- title: "Who cites Language to Logical Form with Neural Attention" description: "255 papers of the Elamur Research library cite «Language to Logical Form with Neural Attention», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/dong-2016-language-logical-form-neural-attention/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/dong-2016-language-logical-form-neural-attention/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Language to Logical Form with Neural Attention](https://md.research.elamur.ai/free/en/papers/dong-2016-language-logical-form-neural-attention/) / cited by # Who cites «Language to Logical Form with Neural Attention» 255 papers of our library cite it (of the 140,884 whose bibliographies we read) · 13 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/dong-2016-language-logical-form-neural-attention/) 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. [**TaPas: Weakly Supervised Table Parsing via Pre-training**Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.*2020 · 844 citations*](https://md.research.elamur.ai/free/en/papers/herzig-2020-tapas-weakly-supervised-table-parsing/) 3. [**Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism**Xiangrong Zeng, Daojian Zeng, Shizhu He, et al.*2018 · 607 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2018-extracting-relational-facts-end-end/) 4. [**TabFact: A Large-scale Dataset for Table-based Fact Verification**Wenhu Chen, Hongmin Wang, Jianshu Chen, et al.*2019 · 508 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-tabfact-large-scale-dataset-table/) 5. [**Learned in Translation: Contextualized Word Vectors**Bryan McCann, James Bradbury, Caiming Xiong, et al.*2017 · 481 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2017-learned-translation-contextualized-word-vectors/) 6. [**DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction**Mohammadreza Pourreza, Davood Rafiei*2023 · 397 citations*](https://md.research.elamur.ai/free/en/papers/pourreza-2023-din-sql-decomposed-context-learning/) 7. [**Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction**Yaojie Lu, Hongyu Lin, Jin Xu, et al.*2021 · 370 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-text2event-controllable-sequence-structure-generation/) 8. [**From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood**Kelvin Guu, Panupong Pasupat, Evan Liu, et al.*2017 · 230 citations*](https://md.research.elamur.ai/free/en/papers/guu-2017-language-programs-bridging-reinforcement-learning/) 9. [**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/) 10. [**Unsupervised Question Decomposition for Question Answering**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/) 11. [**Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations**Rik van Noord, Johan Bos*2017 · 137 citations*](https://md.research.elamur.ai/free/en/papers/noord-2017-neural-semantic-parsing-character-based/) 12. [**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/) 13. [**DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset**Lijie Wang, Ao Zhang, Kun Wu, et al.*2020 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-dusql-large-scale-pragmatic-chinese/) 242 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/dong-2016-language-logical-form-neural-attention/) — Language to Logical Form with Neural Attention