---
title: "Who cites Kai Yang — 622 papers of our library"
description: "622 papers of the Elamur Research library cite the works of Kai Yang, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/kai-yang/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/kai-yang/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Kai Yang](https://md.research.elamur.ai/free/en/authors/kai-yang/) / cited by

# Who cites Kai Yang

622 citations of their works from 622 papers of our library (of the 149,439 whose bibliographies we read) · 131 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Kai Yang](https://md.research.elamur.ai/free/en/authors/kai-yang/)

**1** [2](https://md.research.elamur.ai/free/en/authors/kai-yang/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/kai-yang/cited-by/page/2/)

1. **[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*
2. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
3. **[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*
4. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues? arXiv:2310.06770**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 704 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/)
5. **[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*
6. **[Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/liu-2023-your-code-generated-chatgpt-really/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, et al.*2023 · 648 citations*
7. [**Qwen2.5-Coder Technical Report arXiv:2409.12186**Binyuan Hui, Jian Yang, Zeyu Cui, et al.*2024 · 559 citations*](https://md.research.elamur.ai/free/en/papers/hui-2024-qwen2-5-coder-technical-report/)
8. [**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/)
9. **[FinQA: A Dataset of Numerical Reasoning over Financial Data](https://md.research.elamur.ai/free/en/papers/chen-2021-finqa-dataset-numerical-reasoning-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhiyu Chen, Wenhu Chen, Charese Smiley, et al.*2021 · 513 citations*
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. [**Measuring Coding Challenge Competence With APPS arXiv:2105.09938**Dan Hendrycks, Steven Basart, Saurav Kadavath, et al.*2021 · 457 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-measuring-coding-challenge-competence-apps/)
12. **[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*
13. **[Mind2Web: Towards a Generalist Agent for the Web](https://md.research.elamur.ai/free/en/papers/deng-2023-mind2web-towards-generalist-agent-web/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiang Deng, Yu Gu, Boyuan Zheng, et al.*2023 · 413 citations*
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. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
19. **[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*
20. **[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*
21. **[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*
22. [**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/)
23. [**OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization arXiv:2212.12017**Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, et al.*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2022-opt-iml-scaling-language-model/)
24. **[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*
25. **[Break It Down: A Question Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 222 citations*
26. [**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/)
27. **[CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://md.research.elamur.ai/free/en/papers/ye-2021-crossfit-few-shot-learning-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qinyuan Ye, Bill Yuchen Lin, Xiang Ren*2021 · 210 citations*
28. **[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*
29. [**CodeS: Towards Building Open-source Language Models for Text-to-SQL arXiv:2402.16347**Haoyang Li, Jing Zhang, Hanbing Liu, et al.*2024 · 190 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-codes-towards-building-open-source/)
30. **[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*
31. [**Open Question Answering over Tables and Text arXiv:2010.10439**Wenhu Chen, Ming-Wei Chang, Eva Schlinger, et al.*2020 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-open-question-answering-over-tables/)
32. **[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*
33. [**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/)
34. [**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/)
35. **[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*
36. **[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*
37. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
38. **[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*
39. **[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*
40. **[Open Domain Question Answering over Tables via Dense Retrieval](https://md.research.elamur.ai/free/en/papers/herzig-2021-open-domain-question-answering-over/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jonathan Herzig, Thomas Müller, Syrine Krichene, et al.*2021 · 134 citations*
41. **[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*
42. [**A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability arXiv:2303.13547**Aiwei Liu, Xuming Hu, Lijie Wen, et al.*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-comprehensive-evaluation-chatgpt-s-zero/)
43. [**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/)
44. **[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*
45. **[Natural Language to Code Translation with Execution](https://md.research.elamur.ai/free/en/papers/shi-2022-natural-language-code-translation-execution/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Freda Shi, Daniel Fried, Marjan Ghazvininejad, et al.*2022 · 116 citations*
46. [**HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation arXiv:2108.06712**Zhoujun Cheng, Haoyu Dong, Zhiruo Wang, et al.*2021 · 108 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2021-hitab-hierarchical-table-dataset-question/)
47. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 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. [**Safety Alignment Should Be Made More Than Just a Few Tokens Deep arXiv:2406.05946**Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-safety-alignment-should-made-more/)
50. **[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*
51. **[Task Contamination: Language Models May Not Be Few-Shot Anymore](https://md.research.elamur.ai/free/en/papers/li-2023-task-contamination-language-models-may/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Changmao Li, Jeffrey Flanigan*2023 · 89 citations*
52. [**MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation arXiv:2208.08227**Federico Cassano, John Gouwar, Daniel Nguyen, et al.*2022 · 88 citations*](https://md.research.elamur.ai/free/en/papers/cassano-2022-multipl-e-scalable-extensible-approach/)
53. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
54. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
55. [**LLMs Get Lost In Multi-Turn Conversation arXiv:2505.06120**Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, et al.*2025 · 82 citations*](https://md.research.elamur.ai/free/en/papers/laban-2025-llms-get-lost-multi-turn/)
56. [**Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations arXiv:2303.18027**Jungo Kasai, Yuhei Kasai, Keisuke Sakaguchi, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2023-evaluating-gpt-4-chatgpt-japanese/)
57. [**Multi-VALUE: A Framework for Cross-Dialectal English NLP**Caleb Ziems, William Held, Jingfeng Yang, et al.*2023 · 76 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2023-multi-value-framework-cross-dialectal/)
58. [**Large Language Models as Analogical Reasoners arXiv:2310.01714**Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/)
59. **[MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/wang-2025-mac-sql-multi-agent-collaborative/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bing Wang, Changyu Ren, Jian Yang, et al.*2025 · 68 citations*
60. [**Learning by Distilling Context arXiv:2209.15189**Charlie Snell, Dan Klein, Ruiqi Zhong*2022 · 67 citations*](https://md.research.elamur.ai/free/en/papers/snell-2022-learning-distilling-context/)
61. **[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*
62. **[PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://md.research.elamur.ai/free/en/papers/wei-2025-plangenllms-modern-survey-llm-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wei, Zihao Zhang, Shenghua He, et al.*2025 · 55 citations*
63. [**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/)
64. **[MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation](https://md.research.elamur.ai/free/en/papers/lee-2025-mcs-sql-leveraging-multiple-prompts/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Dongjun Lee, Choongwon Park, Jaehyuk Kim, et al.*2025 · 42 citations*
65. [**Can Language Models Solve Olympiad Programming? arXiv:2404.10952**Quan Shi, Michael Tang, Karthik Narasimhan, et al.*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/shi-2024-language-models-solve-olympiad-programming/)
66. **[When is Tree Search Useful for LLM Planning? It Depends on the Discriminator](https://md.research.elamur.ai/free/en/papers/chen-2024-when-is-tree-search-useful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziru Chen, Michael White, Ray Mooney, et al.*2024 · 28 citations*
67. **[L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2024-l2ceval-evaluating-language-code-generation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.*2024 · 27 citations*
68. **[A Survey on Evaluation of LLM-based Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-survey-evaluation-llm-based-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaf Yehudai, Lilach Eden, Alan Li, et al.*2026 · 21 citations*
69. **[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*
70. **[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*
71. **[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*
72. **[NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Queries](https://md.research.elamur.ai/free/en/papers/zhang-2024-naturalcodebench-examining-coding-performance-mismatch/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shudan Zhang, Hanlin Zhao, Xiao Liu, et al.*2024 · 17 citations*
73. **[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*
74. [**Qwen3-Coder-Next Technical Report arXiv:2603.00729**Ruisheng Cao, Mouxiang Chen, Jiawei Chen, et al.*2026 · 15 citations*](https://md.research.elamur.ai/free/en/papers/cao-2026-qwen3-coder-next-technical/)
75. **[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*
76. [**Zero and Few-shot Semantic Parsing with Ambiguous Inputs arXiv:2306.00824**Elias Stengel-Eskin, Kyle Rawlins, Benjamin Van Durme*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/stengel-eskin-2023-zero-few-shot-semantic-parsing/)
77. **[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*
78. **[SR-LLM: Rethinking the Structured Representation in Large Language Model](https://md.research.elamur.ai/free/en/papers/zhang-2025-sr-llm-rethinking-structured-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahuan Zhang, Tianheng Wang, Hanqing Wu, et al.*2025 · 11 citations*
79. **[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*
80. **[TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-tableeval-real-world-benchmark-complex/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junnan Zhu, Jingyi Wang, Bohan Yu, et al.*2025 · 7 citations*
81. **[Weaver: Interweaving SQL and LLM for Table Reasoning](https://md.research.elamur.ai/free/en/papers/khoja-2025-weaver-interweaving-sql-llm-table/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rohit Khoja, Devanshu Gupta, Yanjie Fu, et al.*2025 · 6 citations*
82. **[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*
83. **[When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables](https://md.research.elamur.ai/free/en/papers/ye-2026-when-tableqa-meets-noise-dual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shenghao Ye, Yu Guo, Dong Jin, et al.*2026 · 4 citations*
84. **[LitE-SQL: A Lightweight and Efficient Text-to-SQL Framework with Vector-based Schema Linking and Execution-Guided Self-Correction](https://md.research.elamur.ai/free/en/papers/piao-2026-lite-sql-lightweight-efficient-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shengmin Piao, Jieun Lee, Sanghyun Park*2026 · 3 citations*
85. **[MT-OSC: Path for LLMs that Get Lost in Multi-Turn Conversation](https://md.research.elamur.ai/free/en/papers/singh-2026-mt-osc-path-llms-that/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jyotika Singh, Fang Tu, Miguel Ballesteros, et al.*2026 · 3 citations*
86. **[RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking](https://md.research.elamur.ai/free/en/papers/zou-2026-rag-over-tables-hierarchical-memory/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaru Zou, Dongqi Fu, Sirui Chen, et al.*2026 · 3 citations*
87. **[SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes](https://md.research.elamur.ai/free/en/papers/xie-2026-sde-sql-enhancing-text-sql/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxuan Xie, Yaxun Dai, Wenhao Jiang*2026 · 3 citations*
88. **[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*
89. **[Mistake Notebook Learning: Batch-Clustered Failures for Training-Free Agent Adaptation](https://md.research.elamur.ai/free/en/papers/su-2026-mistake-notebook-learning-batch-clustered/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanbo Su, Yingfang Zhang, Hao Luo, et al.*2026 · 2 citations*
90. **[Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation](https://md.research.elamur.ai/free/en/papers/zhou-2026-table-question-answering-era-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhou, Bolei Ma, Annemarie Friedrich, et al.*2026 · 2 citations*
91. [**Prompt Engineering Techniques for Context-dependent Text-to-SQL in Arabic arXiv:2511.20677**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/)
92. **[Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists](https://md.research.elamur.ai/free/en/papers/pietruszka-2026-can-models-help-us-create/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michał Pietruszka, Łukasz Borchmann, Aleksander Jędrosz, et al.*2026 · 1 citation*
93. **[PV-SQL: Synergizing Database Probing and Rule-based Verification for Text-to-SQL Agents](https://md.research.elamur.ai/free/en/papers/tian-2026-pv-sql-synergizing-database-probing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Tian, Tianyi Zhang*2026 · 1 citation*
94. **[Rethinking Schema Linking: A Context-Aware Bidirectional Retrieval Approach for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/nahid-2026-rethinking-schema-linking-context-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Mahadi Hasan Nahid, Davood Rafiei, Weiwei Zhang, et al.*2026 · 1 citation*
95. [**AraSpider: Democratizing Arabic-to-SQL arXiv:2402.07448**Ahmed Heakl; Youssef Mohamed;, Ahmed B. Zaky*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/heakl-2024-araspider-democratizing-arabic-sql/)
96. **[Adaptive Text2GQL: Integrating Structural Twig Linking and Evolutionary In-Context Learning](https://md.research.elamur.ai/free/en/papers/niu-2026-adaptive-text2gql-integrating-structural-twig/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fang Niu, Chaokun Wang, Hang Zhang, et al.*2026*
97. **[Asking language models how to represent data for fine-tuning](https://md.research.elamur.ai/free/en/papers/singh-2026-asking-language-models-how-represent/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Usneek Singh, Ananya Singha, Abhijeet Awasthi, et al.*2026*
98. **[Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-static-rules-automated-discovery/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanqing Wang, Yongdong Chi, Jian Yang, et al.*2026*
99. **[Bidirectional Semantic Enhancement for Schema Routing Across Large-Scale Databases](https://md.research.elamur.ai/free/en/papers/wu-2026-bidirectional-semantic-enhancement-schema-routing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyang Wu, Xiaoliang Wang, Cam-Tu Nguyen*2026*
100. **[CLARITY: A Framework and Benchmark for Conversational Language Ambiguity and Unanswerability in Interactive NL2SQL Systems](https://md.research.elamur.ai/free/en/papers/sarwar-2026-clarity-framework-benchmark-conversational-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tabinda Sarwar, Farhad Moghimifar, Cong Duy Vu Hoang, et al.*2026*

**1** [2](https://md.research.elamur.ai/free/en/authors/kai-yang/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/kai-yang/cited-by/page/2/)

- [← back to](https://md.research.elamur.ai/free/en/authors/kai-yang/) — Kai Yang