🔗 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»

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. Code Llama: Open Foundation Models for CodearXiv:2308.12950Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.2024 · 1,430 citations
3. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (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 StudyACM 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 ModelsACM Transactions on Software Engineering and MethodologyXue Jiang, Yihong Dong, Lecheng Wang, et al.2023 · 223 citations
6. Large Language Models as Commonsense Knowledge for Large-Scale Task PlanningConference on Neural Information Processing Systems (NeurIPS)Zirui Zhao, Wee Sun Lee, David Hsu2023 · 153 citations
7. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
8. Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language ModelsarXiv:2408.00724Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.2024 · 122 citations
9. 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
10. ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMsarXiv:2402.11753Fengqing Jiang, Zhangchen Xu, Luyao Niu, et al.2024 · 83 citations
11. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
12. Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?Annual Meeting of the Association for Computational Linguistics (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 DiscriminatorAnnual Meeting of the Association for Computational Linguistics (ACL)Ziru Chen, Michael White, Ray Mooney, et al.2024 · 28 citations
14. ALGO: Synthesizing Algorithmic Programs with LLM-Generated Oracle VerifiersarXiv:2305.14591Kexun Zhang, Danqing Wang, Jingtao Xia, et al.2023 · 19 citations
15. Benchmarking Language Model Creativity: A Case Study on Code GenerationConference of the North American Chapter of the Association for Computational Linguistics (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 DebuggingarXiv:2410.01215Yuling Shi, Songsong Wang, Chengcheng Wan, et al.2024 · 15 citations
17. AlphaOne: Reasoning Models Thinking Slow and Fast at Test TimeConference on Empirical Methods in Natural Language Processing (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 RefinementAnnual Meeting of the Association for Computational Linguistics (ACL)Zexu Sun, Yongcheng Zeng, Erxue Min, et al.2026
19. MavenCoder: Competitive Code Generation via Model Adaptive Planning Strategies and Multi-Perspective Verification EnhancementAnnual Meeting of the Association for Computational Linguistics (ACL)ZhenChun Xu, Yi Cai, Dajun Zheng, et al.2026
20. SeDev: Structured Semantic Exploration for LLM-Driven Code GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Ronghui Yang, Jie Liu, Jiajie Zeng, et al.2026
21. Uncertainty-Aware Test-Time Search for Optimization Problem SolvingAnnual Meeting of the Association for Computational Linguistics (ACL)Linlin Yu, Xujiang Zhao, Dong Li, et al.2026

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

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