🔗 Who cites «Natural Language to Code Translation with Execution»

70 papers of our library cite it (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · ← back to «Natural Language to Code Translation with Execution»

1. Self-Consistency Improves Chain of Thought Reasoning in Language ModelsarXiv:2203.11171Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 3,121 citations
2. Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
3. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
4. Language Models are Multilingual Chain-of-Thought ReasonersarXiv:2210.03057Freda Shi, Mirac Suzgun, Markus Freitag, et al.2022 · 494 citations
5. Binding Language Models in Symbolic LanguagesarXiv:2210.02875Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.2022 · 170 citations
6. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 161 citations
7. FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain ScenariosarXiv:2307.13528I-Chun Chern, Steffi Chern, Shiqi Chen, et al.2023 · 160 citations
8. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations
9. Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-steparXiv:2402.16906Li Zhong, Zilong Wang, Jingbo Shang2024 · 124 citations
10. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
11. Compositional Exemplars for In-context LearningarXiv:2302.05698Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, et al.2023 · 120 citations
12. INSIDE: LLMs' Internal States Retain the Power of Hallucination DetectionarXiv:2402.03744Chao Chen, Kai Liu, Ze Chen, et al.2024 · 108 citations
13. Self-Edit: Fault-Aware Code Editor for Code GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Kechi Zhang, Zhuo Li, Jia Li, et al.2023 · 105 citations
14. InterCode: Standardizing and Benchmarking Interactive Coding with Execution FeedbackConference on Neural Information Processing Systems (NeurIPS)John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.2023 · 95 citations
15. Universal Self-Consistency for Large Language Model GenerationarXiv:2311.17311Xinyun Chen, Renat Aksitov, Uri Alon, et al.2023 · 92 citations
16. Multi-lingual Evaluation of Code Generation ModelsarXiv:2210.14868Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, et al.2022 · 86 citations
17. Is Self-Repair a Silver Bullet for Code Generation?arXiv:2306.09896Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, et al.2024 · 82 citations
18. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
19. Dynamic Cheatsheet: Test-Time Learning with Adaptive MemoryConference of the European Chapter of the Association for Computational Linguistics (EACL)Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi, et al.2026 · 37 citations
20. L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.2024 · 27 citations
21. CodeTree: Agent-guided Tree Search for Code Generation with Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jierui Li, Hung Le, Yingbo Zhou, et al.2025 · 21 citations
22. ALGO: Synthesizing Algorithmic Programs with LLM-Generated Oracle VerifiersarXiv:2305.14591Kexun Zhang, Danqing Wang, Jingtao Xia, et al.2023 · 19 citations
23. CoAct: Co-Active LLM Preference Learning with Human-AI SynergyAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.2026 · 1 citation
24. GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy InputsFindings of the Association for Computational LinguisticsZhengxin Zhang, Chengyu Huang, Xufu Liu, et al.2026
25. Learning from Near-Misses: Error-Aware Contrastive Few-Shot Learning for NL2FormulaAnnual Meeting of the Association for Computational Linguistics (ACL)Zhihao Shuai, Yiyun Chen, Maolin Ma, et al.2026
26. TableMBR: Minimum Bayes Risk Table Generation Based on Structural ConsistencyAnnual Meeting of the Association for Computational Linguistics (ACL)Daiki Yoshida, Hiroyuki Deguchi, Yusuke Sakai, et al.2026

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