--- title: "Who cites Planning with Large Language — 75 citing papers" description: "75 papers of the Elamur Research library cite «Planning with Large Language Models for Code Generation», found in their bibliographies; the…" canonical: "https://research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Planning with Large Language Models for Code…](https://md.research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/) / cited by # Who cites «Planning with Large Language Models for Code Generation» 75 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «Planning with Large Language Models for Code Generation»](https://md.research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/) 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. [**Code Llama: Open Foundation Models for Code arXiv:2308.12950**Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.*2024 · 1,430 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/) 3. **[s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.*2025 · 608 citations* 4. **[Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study](https://md.research.elamur.ai/free/en/papers/sui-2023-table-meets-llm-large-language/) [ACM International Conference on Web Search and Data Mining (WSDM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-web-search-and-data-mining-wsdm/)**Yuan Sui, Mengyu Zhou, Mingjie Zhou, et al.*2023 · 235 citations* 5. **[Self-planning Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-self-planning-code-generation-large/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Xue Jiang, Yihong Dong, Lecheng Wang, et al.*2023 · 223 citations* 6. **[Large Language Models as Commonsense Knowledge for Large-Scale Task Planning](https://md.research.elamur.ai/free/en/papers/zhao-2023-large-language-models-commonsense-knowledge/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zirui Zhao, Wee Sun Lee, David Hsu*2023 · 153 citations* 7. [**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/) 8. [**Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models arXiv:2408.00724**Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-inference-scaling-laws-empirical-analysis/) 9. **[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* 10. [**ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs arXiv:2402.11753**Fengqing Jiang, Zhangchen Xu, Luyao Niu, et al.*2024 · 83 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-artprompt-ascii-art-based-jailbreak/) 11. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/) 12. **[Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?](https://md.research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2025 · 38 citations* 13. **[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* 14. [**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/) 15. **[Benchmarking Language Model Creativity: A Case Study on Code Generation](https://md.research.elamur.ai/free/en/papers/lu-2025-benchmarking-language-model-creativity-case/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yining Lu, Dixuan Wang, Tianjian Li, et al.*2025 · 17 citations* 16. [**From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging arXiv:2410.01215**Yuling Shi, Songsong Wang, Chengcheng Wan, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shi-2024-code-correctness-closing-last-mile/) 17. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyu Zhang, Runpei Dong, Han Wang, et al.*2025 · 10 citations* 18. **[Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement](https://md.research.elamur.ai/free/en/papers/sun-2026-learning-cognition-enhancing-rl-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zexu Sun, Yongcheng Zeng, Erxue Min, et al.*2026* 19. **[MavenCoder: Competitive Code Generation via Model Adaptive Planning Strategies and Multi-Perspective Verification Enhancement](https://md.research.elamur.ai/free/en/papers/xu-2026-mavencoder-competitive-code-generation-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ZhenChun Xu, Yi Cai, Dajun Zheng, et al.*2026* 20. **[SeDev: Structured Semantic Exploration for LLM-Driven Code Generation](https://md.research.elamur.ai/free/en/papers/yang-2026-sedev-structured-semantic-exploration-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ronghui Yang, Jie Liu, Jiajie Zeng, et al.*2026* 21. **[Uncertainty-Aware Test-Time Search for Optimization Problem Solving](https://md.research.elamur.ai/free/en/papers/yu-2026-uncertainty-aware-test-time-search/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linlin Yu, Xujiang Zhao, Dong Li, et al.*2026* 54 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2023-planning-large-language-models-code/) — Planning with Large Language Models for Code Generation