---
title: "Who cites Process Supervision-Guided — 12 citing papers"
description: "12 papers of the Elamur Research library cite «Process Supervision-Guided Policy Optimization for Code Generation», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/dai-2024-process-supervision-guided-policy-optimization/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/dai-2024-process-supervision-guided-policy-optimization/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Process Supervision-Guided Policy Optimization…](https://md.research.elamur.ai/free/en/papers/dai-2024-process-supervision-guided-policy-optimization/) / cited by

# Who cites «Process Supervision-Guided Policy Optimization for Code Generation»

12 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «Process Supervision-Guided Policy Optimization for Code Generation»](https://md.research.elamur.ai/free/en/papers/dai-2024-process-supervision-guided-policy-optimization/)

1. [**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/)
2. **[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*
3. **[OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-opengenalign-preference-dataset-benchmark-trustworthy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanning Zhang, Juntong Song, Juno Zhu, et al.*2026 · 2 citations*
4. **[A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage](https://md.research.elamur.ai/free/en/papers/zheng-2026-comprehensive-survey-process-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Congmin Zheng, Jiachen Zhu, Zhuoying Ou, et al.*2026*
5. **[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*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/dai-2024-process-supervision-guided-policy-optimization/) — Process Supervision-Guided Policy Optimization for Code Generation