--- title: "Who cites Zheng Wu — 24 papers of our library" description: "24 papers of the Elamur Research library cite the works of Zheng Wu, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/zheng-wu/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zheng-wu/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Zheng Wu](https://md.research.elamur.ai/free/en/authors/zheng-wu/) / cited by # Who cites Zheng Wu 24 citations of their works from 24 papers of our library (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← Zheng Wu](https://md.research.elamur.ai/free/en/authors/zheng-wu/) 1. [**OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework arXiv:2405.11143**Jian Hu, Xibin Wu, Wei Shen, et al.*2024 · 140 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-openrlhf-easy-use-scalable/) 2. [**REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization arXiv:2501.03262**Jian Hu, Jason Klein Liu, Haotian Xu, et al.*2025 · 104 citations*](https://md.research.elamur.ai/free/en/papers/hu-2025-reinforce-stabilizing-critic-free-policy/) 3. [**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/) 4. [**VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks arXiv:2504.05118**Yu Yue, Yufeng Yuan, Qiying Yu, et al.*2025 · 68 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-vapo-efficient-reliable-reinforcement-learning/) 5. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/) 6. [**Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning arXiv:2504.13914**ByteDance Seed, Jiaze Chen, Tiantian Fan, et al.*2025 · 62 citations*](https://md.research.elamur.ai/free/en/papers/bytedance-seed-2025-seed1-5-thinking-advancing/) 7. [**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/) 8. [**A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility arXiv:2504.07086**Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/hochlehnert-2025-sober-look-progress-language-model/) 9. **[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* 10. **[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* 11. **[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* 12. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026* 13. **[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* 11 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/zheng-wu/) — Zheng Wu