--- title: "Who cites NExT: Teaching Large Language — 25 citing papers" description: "25 papers of the Elamur Research library cite «NExT: Teaching Large Language Models to Reason about Code Execution», found in their…" canonical: "https://research.elamur.ai/free/en/papers/ni-2024-next-teaching-large-language-models/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ni-2024-next-teaching-large-language-models/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [NExT: Teaching Large Language Models to Reason…](https://md.research.elamur.ai/free/en/papers/ni-2024-next-teaching-large-language-models/) / cited by # Who cites «NExT: Teaching Large Language Models to Reason about Code Execution» 25 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «NExT: Teaching Large Language Models to Reason about Code Execution»](https://md.research.elamur.ai/free/en/papers/ni-2024-next-teaching-large-language-models/) 1. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/) 2. [**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/) 3. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/) 4. [**CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction arXiv:2502.07316**Junlong Li, Daya Guo, Dejian Yang, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-codei-o-condensing-reasoning/) 5. **[Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-code-think-think-code-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dayu Yang, Tianyang Liu, Daoan Zhang, et al.*2025 · 19 citations* 6. [**Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models arXiv:2412.02980**Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-surveying-effects-quality-diversity-complexity/) 7. **[CodePRM: Execution Feedback-enhanced Process Reward Model for Code Generation](https://md.research.elamur.ai/free/en/papers/li-2025-codeprm-execution-feedback-enhanced-process/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyao Li, Xinyi Dai, Xiangyang Li, et al.*2025 · 15 citations* 8. **[From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging](https://md.research.elamur.ai/free/en/papers/shi-2024-code-correctness-closing-last-mile/) [IEEE/ACM International Conference on Software Engineering (ICSE)](https://md.research.elamur.ai/free/en/venues/ieee-acm-international-conference-on-software-engineering-icse/)**Yuling Shi, Songsong Wang, Chengcheng Wan, et al.*2024 · 15 citations* 9. **[EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking](https://md.research.elamur.ai/free/en/papers/wei-2025-equibench-benchmarking-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anjiang Wei, Jiannan Cao, Ran Li, et al.*2025 · 8 citations* 10. **[ExecVerify: White-Box RL with Verifiable Stepwise Rewards for Code Execution Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2026-execverify-white-box-rl-verifiable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingxiao Tang, He Ye, Zhaoyang Chu, et al.*2026 · 1 citation* 11. **[Think Like You Execute: Verifiable Chain of Thought from Program Traces](https://md.research.elamur.ai/free/en/papers/thakur-2026-think-like-you-execute-verifiable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shailja Thakur, Vaibhav Saxena, Rohan Kulkarni, et al.*2026* 14 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/ni-2024-next-teaching-large-language-models/) — NExT: Teaching Large Language Models to Reason about Code Execution