---
title: "Who cites Natural Language to Code Translation with Execution"
description: "70 papers of the Elamur Research library cite «Natural Language to Code Translation with Execution», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/shi-2022-natural-language-code-translation-execution/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/shi-2022-natural-language-code-translation-execution/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Natural Language to Code Translation with…](https://md.research.elamur.ai/free/en/papers/shi-2022-natural-language-code-translation-execution/) / cited by

# 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»](https://md.research.elamur.ai/free/en/papers/shi-2022-natural-language-code-translation-execution/)

1. [**Self-Consistency Improves Chain of Thought Reasoning in Language Models arXiv:2203.11171**Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.*2022 · 3,121 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-self-consistency-improves-chain-thought/)
2. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
3. [**Large Language Models Can Be Easily Distracted by Irrelevant Context arXiv:2302.00093**Freda Shi, Xinyun Chen, Kanishka Misra, et al.*2023 · 534 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-large-language-models-easily-distracted/)
4. [**Language Models are Multilingual Chain-of-Thought Reasoners arXiv:2210.03057**Freda Shi, Mirac Suzgun, Markus Freitag, et al.*2022 · 494 citations*](https://md.research.elamur.ai/free/en/papers/shi-2022-language-models-multilingual-chain-thought/)
5. [**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/)
6. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/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 Scenarios arXiv:2307.13528**I-Chun Chern, Steffi Chern, Shiqi Chen, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chern-2023-factool-factuality-detection-generative-ai/)
8. [**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/)
9. [**Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step arXiv:2402.16906**Li Zhong, Zilong Wang, Jingbo Shang*2024 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-debug-like-human-large-language/)
10. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
11. [**Compositional Exemplars for In-context Learning arXiv:2302.05698**Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-compositional-exemplars-context-learning/)
12. [**INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection arXiv:2402.03744**Chao Chen, Kai Liu, Ze Chen, et al.*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-inside-llms-internal-states-retain/)
13. **[Self-Edit: Fault-Aware Code Editor for Code Generation](https://md.research.elamur.ai/free/en/papers/zhang-2023-self-edit-fault-aware-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kechi Zhang, Zhuo Li, Jia Li, et al.*2023 · 105 citations*
14. **[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*
15. [**Universal Self-Consistency for Large Language Model Generation arXiv:2311.17311**Xinyun Chen, Renat Aksitov, Uri Alon, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-universal-self-consistency-large-language/)
16. [**Multi-lingual Evaluation of Code Generation Models arXiv:2210.14868**Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, et al.*2022 · 86 citations*](https://md.research.elamur.ai/free/en/papers/athiwaratkun-2022-multi-lingual-evaluation-code-generation/)
17. [**Is Self-Repair a Silver Bullet for Code Generation? arXiv:2306.09896**Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, et al.*2024 · 82 citations*](https://md.research.elamur.ai/free/en/papers/olausson-2024-self-repair-silver-bullet-code/)
18. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
19. **[Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory](https://md.research.elamur.ai/free/en/papers/suzgun-2026-dynamic-cheatsheet-test-time-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi, et al.*2026 · 37 citations*
20. **[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*
21. **[CodeTree: Agent-guided Tree Search for Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2025-codetree-agent-guided-tree-search/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jierui Li, Hung Le, Yingbo Zhou, et al.*2025 · 21 citations*
22. [**ALGO: Synthesizing Algorithmic Programs with LLM-Generated Oracle Verifiers arXiv:2305.14591**Kexun Zhang, Danqing Wang, Jingtao Xia, et al.*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-algo-synthesizing-algorithmic-programs-llm/)
23. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.*2026 · 1 citation*
24. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
25. **[Learning from Near-Misses: Error-Aware Contrastive Few-Shot Learning for NL2Formula](https://md.research.elamur.ai/free/en/papers/shuai-2026-learning-near-misses-error-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhihao Shuai, Yiyun Chen, Maolin Ma, et al.*2026*
26. **[TableMBR: Minimum Bayes Risk Table Generation Based on Structural Consistency](https://md.research.elamur.ai/free/en/papers/yoshida-2026-tablembr-minimum-bayes-risk-table/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daiki Yoshida, Hiroyuki Deguchi, Yusuke Sakai, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/shi-2022-natural-language-code-translation-execution/) — Natural Language to Code Translation with Execution