---
title: "Who cites Seq2SQL: Generating — 493 citing papers"
description: "493 papers of the Elamur Research library cite «Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement…"
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---
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# Who cites «Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning»

493 papers of our library cite it (of the 149,439 whose bibliographies we read) · 78 with a page here, the most cited first · [← back to «Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning»](https://md.research.elamur.ai/free/en/papers/zhong-2017-seq2sql-generating-structured-queries-natural/)

1. [**LoRA: Low-Rank Adaptation of Large Language Models arXiv:2106.09685**Edward J. Hu, Yelong Shen, Phillip Wallis, et al.*2021 · 8,661 citations*](https://md.research.elamur.ai/free/en/papers/hu-2021-lora-low-rank-adaptation-large/)
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
3. **[Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Yu, Rui Zhang, Kai Yang, et al.*2018 · 1,602 citations*
4. **[TaPas: Weakly Supervised Table Parsing via Pre-training](https://md.research.elamur.ai/free/en/papers/herzig-2020-tapas-weakly-supervised-table-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.*2020 · 847 citations*
5. **[The Web as a Knowledge-Base for Answering Complex Questions](https://md.research.elamur.ai/free/en/papers/talmor-2018-web-as-knowledge-base-answering/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Alon Talmor, Jonathan Berant*2018 · 819 citations*
6. **[RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers](https://md.research.elamur.ai/free/en/papers/wang-2020-rat-sql-relation-aware-schema/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bailin Wang, Richard Shin, Xiaodong Liu, et al.*2020 · 753 citations*
7. **[TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 692 citations*
8. [**The Natural Language Decathlon: Multitask Learning as Question Answering arXiv:1806.08730**Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, et al.*2018 · 545 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2018-natural-language-decathlon-multitask-learning/)
9. [**TabFact: A Large-scale Dataset for Table-based Fact Verification arXiv:1909.02164**Wenhu Chen, Hongmin Wang, Jianshu Chen, et al.*2019 · 515 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-tabfact-large-scale-dataset-table/)
10. **[Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation](https://md.research.elamur.ai/free/en/papers/gao-2023-text-sql-empowered-large-language/) [Proceedings of the VLDB Endowment](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-vldb-endowment/)**Dawei Gao, Haibin Wang, Yaliang Li, et al.*2023 · 463 citations*
11. **[Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs](https://md.research.elamur.ai/free/en/papers/li-2023-llm-already-serve-database-interface/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jinyang Li, Binyuan Hui, Ge Qu, et al.*2023 · 433 citations*
12. [**AgentBench: Evaluating LLMs as Agents arXiv:2308.03688**Xiao Liu, Hao Yu, Hanchen Zhang, et al.*2023 · 432 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-agentbench-evaluating-llms-agents/)
13. [**WebArena: A Realistic Web Environment for Building Autonomous Agents arXiv:2307.13854**Shuyan Zhou, Frank F. Xu, Hao Zhu, et al.*2023 · 432 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-webarena-realistic-web-environment-building/)
14. **[UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models](https://md.research.elamur.ai/free/en/papers/xie-2022-unifiedskg-unifying-multi-tasking-structured/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianbao Xie, Chen Henry Wu, Peng Shi, et al.*2022 · 407 citations*
15. **[DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction](https://md.research.elamur.ai/free/en/papers/pourreza-2023-din-sql-decomposed-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mohammadreza Pourreza, Davood Rafiei*2023 · 401 citations*
16. **[TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance](https://md.research.elamur.ai/free/en/papers/zhu-2021-tat-qa-question-answering-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengbin Zhu, Wenqiang Lei, Youcheng Huang, et al.*2021 · 397 citations*
17. [**HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data arXiv:2004.07347**Wenhu Chen, Hanwen Zha, Zhiyu Chen, et al.*2020 · 382 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/)
18. [**Augmented Language Models: a Survey arXiv:2302.07842**Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-augmented-language-models-survey/)
19. [**UL2: Unifying Language Learning Paradigms arXiv:2205.05131**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 347 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
20. **[CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/le-2022-coderl-mastering-code-generation-through/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.*2022 · 297 citations*
21. **[RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/li-2023-resdsql-decoupling-schema-linking-skeleton/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Haoyang Li, Jing Zhang, Cuiping Li, et al.*2023 · 277 citations*
22. **[Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing](https://md.research.elamur.ai/free/en/papers/bogin-2019-representing-schema-structure-graph-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ben Bogin, Jonathan Berant, Matt Gardner*2019 · 272 citations*
23. **[Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Victoria Lin, Richard Socher, Caiming Xiong*2020 · 263 citations*
24. **[CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases](https://md.research.elamur.ai/free/en/papers/yu-2019-cosql-conversational-text-sql-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Yu, Rui Zhang, Heyang Er, et al.*2019 · 262 citations*
25. [**TAPEX: Table Pre-training via Learning a Neural SQL Executor arXiv:2107.07653**Qian Liu, Bei Chen, Jiaqi Guo, et al.*2021 · 255 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-tapex-table-pre-training-learning/)
26. **[A Discrete Hard EM Approach for Weakly Supervised Question Answering](https://md.research.elamur.ai/free/en/papers/min-2019-discrete-hard-em-approach-weakly/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Danqi Chen, Hannaneh Hajishirzi, et al.*2019 · 237 citations*
27. **[SParC: Cross-Domain Semantic Parsing in Context](https://md.research.elamur.ai/free/en/papers/yu-2019-sparc-cross-domain-semantic-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tao Yu, Rui Zhang, Michihiro Yasunaga, et al.*2019 · 228 citations*
28. [**Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning arXiv:2209.14610**Pan Lu, Liang Qiu, Kai-Wei Chang, et al.*2022 · 219 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-dynamic-prompt-learning-policy-gradient/)
29. [**TinyStories: How Small Can Language Models Be and Still Speak Coherent English?**Ronen Eldan, Yuanzhi Li*2023 · 213 citations*](https://md.research.elamur.ai/free/en/papers/eldan-2023-tinystories-small-language-models-still/)
30. **[What matters when building vision-language models?](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 212 citations*
31. **[Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 208 citations*
32. **[LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations](https://md.research.elamur.ai/free/en/papers/cao-2021-lgesql-line-graph-enhanced-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruisheng Cao, Lu Chen, Zhi Chen, et al.*2021 · 191 citations*
33. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
34. **[Large Language Models are few(1)-shot Table Reasoners](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-are-few/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhu Chen*2023 · 182 citations*
35. **[Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions](https://md.research.elamur.ai/free/en/papers/zhang-2019-editing-based-sql-query-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rui Zhang, Tao Yu, Heyang Er, et al.*2019 · 177 citations*
36. [**Binding Language Models in Symbolic Languages arXiv:2210.02875**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 170 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/)
37. **[Quark: Controllable Text Generation with Reinforced Unlearning](https://md.research.elamur.ai/free/en/papers/lu-2022-quark-controllable-text-generation-reinforced/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ximing Lu, Sean Welleck, Jack Hessel, et al.*2022 · 170 citations*
38. [**SantaCoder: don't reach for the stars! arXiv:2301.03988**Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.*2023 · 167 citations*](https://md.research.elamur.ai/free/en/papers/allal-2023-santacoder-don-t-reach-stars/)
39. **[Structure-Grounded Pretraining for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.*2021 · 167 citations*
40. [**DART: Open-Domain Structured Data Record to Text Generation arXiv:2007.02871**Linyong Nan, Dragomir Radev, Rui Zhang, et al.*2020 · 161 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-dart-open-domain-structured-data/)
41. **[RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases](https://md.research.elamur.ai/free/en/papers/choi-2021-ryansql-recursively-applying-sketch-based/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**DongHyun Choi, Myeong Cheol Shin, EungGyun Kim, et al.*2021 · 157 citations*
42. **[Towards Robustness of Text-to-SQL Models against Synonym Substitution](https://md.research.elamur.ai/free/en/papers/gan-2021-robustness-text-sql-models-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujian Gan, Xinyun Chen, Qiuping Huang, et al.*2021 · 143 citations*
43. **[Grounded Adaptation for Zero-shot Executable Semantic Parsing](https://md.research.elamur.ai/free/en/papers/zhong-2020-grounded-adaptation-zero-shot-executable/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Victor Zhong, Mike Lewis, Sida I. Wang, et al.*2020 · 136 citations*
44. **[ReFT: Reasoning with Reinforced Fine-Tuning](https://md.research.elamur.ai/free/en/papers/trung-2024-reft-reasoning-reinforced-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luong Trung, Xinbo Zhang, Zhanming Jie, et al.*2024 · 134 citations*
45. **[MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data](https://md.research.elamur.ai/free/en/papers/zhao-2022-multihiertt-numerical-reasoning-over-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Yunxiang Li, Chenying Li, et al.*2022 · 128 citations*
46. [**LEVER: Learning to Verify Language-to-Code Generation with Execution arXiv:2302.08468**Ansong Ni, Srini Iyer, Dragomir Radev, et al.*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/ni-2023-lever-learning-verify-language-code/)
47. **[Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization](https://md.research.elamur.ai/free/en/papers/gan-2021-exploring-underexplored-limitations-cross-domain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yujian Gan, Xinyun Chen, Matthew Purver*2021 · 123 citations*
48. **[Transformers for Tabular Data Representation: A Survey of Models and Applications](https://md.research.elamur.ai/free/en/papers/badaro-2023-transformers-tabular-data-representation-survey/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Gilbert Badaro, Mohammed Saeed, Paolo Papotti*2023 · 104 citations*
49. **[InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback](https://md.research.elamur.ai/free/en/papers/yang-2023-intercode-standardizing-benchmarking-interactive-coding/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.*2023 · 95 citations*
50. **[JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation](https://md.research.elamur.ai/free/en/papers/agashe-2019-juice-large-scale-distantly-supervised/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer*2019 · 75 citations*
51. **[DuSQL: A Large-Scale and Pragmatic Chinese Text-to-SQL Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-dusql-large-scale-pragmatic-chinese/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lijie Wang, Ao Zhang, Kun Wu, et al.*2020 · 64 citations*
52. **[Learning an Executable Neural Semantic Parser](https://md.research.elamur.ai/free/en/papers/cheng-2019-learning-executable-neural-semantic-parser/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Jianpeng Cheng, Siva Reddy, Vijay Saraswat, et al.*2019 · 63 citations*
53. [**Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? arXiv:2406.13121**Jinhyuk Lee, Anthony Chen, Zhuyun Dai, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-long-context-language-models-subsume/)
54. **[XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2024 · 51 citations*
55. [**xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval arXiv:2303.03004**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/khan-2023-xcodeeval-large-scale-multilingual-multitask/)
56. **[Aligning Large Language Models with Human Preferences through Representation Engineering](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-large-language-models-human/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhao Liu, Xiaohua Wang, Muling Wu, et al.*2024 · 37 citations*
57. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
58. [**From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning arXiv:2304.07995**Qian Liu, Fan Zhou, Zhengbao Jiang, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-zero-hero-examining-power-symbolic/)
59. **[SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation](https://md.research.elamur.ai/free/en/papers/ma-2024-spreadsheetbench-towards-challenging-real-world/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zeyao Ma, Bohan Zhang, Jing Zhang, et al.*2024 · 21 citations*
60. **[DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI](https://md.research.elamur.ai/free/en/papers/zhang-2023-dialogstudio-towards-richest-most-diverse/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianguo Zhang, Kun Qian, Zhiwei Liu, et al.*2023 · 21 citations*
61. **[STaR-SQL: Self-Taught Reasoner for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/he-2025-star-sql-self-taught-reasoner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingqian He, Yongliang Shen, Wenqi Zhang, et al.*2025 · 17 citations*
62. **[Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQL](https://md.research.elamur.ai/free/en/papers/yao-2026-arctic-text2sql-r1-simple-rewards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhewei Yao, Guoheng Sun, Łukasz Borchmann, et al.*2026 · 15 citations*
63. **[PRACTIQ: A Practical Conversational Text-to-SQL dataset with Ambiguous and Unanswerable Queries](https://md.research.elamur.ai/free/en/papers/dong-2025-practiq-practical-conversational-text-sql/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mingwen Dong, Nischal Ashok Kumar, Yiqun Hu, et al.*2025 · 15 citations*
64. **[Ar-Spider: Text-to-SQL in Arabic](https://md.research.elamur.ai/free/en/papers/almohaimeed-2024-ar-spider-text-sql-arabic/) [ACM/SIGAPP Symposium on Applied Computing (SAC)](https://md.research.elamur.ai/free/en/venues/acm-sigapp-symposium-on-applied-computing-sac/)**Saleh Almohaimeed, Saad Almohaimeed, Mansour Al Ghanim, et al.*2024 · 13 citations*
65. **[TableLoRA: Low-rank Adaptation on Table Structure Understanding for Large Language Models](https://md.research.elamur.ai/free/en/papers/he-2025-tablelora-low-rank-adaptation-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi He, Yihao Liu, Mengyu Zhou, et al.*2025 · 8 citations*
66. **[Patient-Similarity Cohort Reasoning in Clinical Text-to-SQL](https://md.research.elamur.ai/free/en/papers/shen-2026-patient-similarity-cohort-reasoning-clinical/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yifei Shen, Yilun Zhao, Justice Ou, et al.*2026 · 4 citations*
67. [**DeepSTL — From English Requirements to Signal Temporal Logic arXiv:2109.10294**Jie He, Ezio Bartocci, Dejan Ničkovic, et al.*2021 · 4 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-deepstl-english-requirements-signal-temporal/)
68. **[ClaimDB: A Fact Verification Benchmark over Large Structured Data](https://md.research.elamur.ai/free/en/papers/theologitis-2026-claimdb-fact-verification-benchmark-over/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Theologitis, Preetam Prabhu Srikar Dammu, Chirag Shah, et al.*2026 · 2 citations*
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