--- title: "Zhihong Shao — papers of 2024 — 5 papers, the most cited first" description: "Zhihong Shao — papers of 2024: 5 papers on Elamur Research, the most cited first — what each work is about in our own words." canonical: "https://research.elamur.ai/free/en/authors/zhihong-shao/year/2024/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhihong-shao/year/2024/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Zhihong Shao](https://md.research.elamur.ai/free/en/authors/zhihong-shao/) / 2024 # Zhihong Shao — papers of 2024 — 5 papers, the most cited first 5 papers · [all years of Zhihong Shao](https://md.research.elamur.ai/free/en/authors/zhihong-shao/#years) - [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models arXiv:2402.03300](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/) — Zhihong Shao, Peiyi Wang, Qihao Zhu, et al. · 2024 · 2,115 citations **[Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations](https://md.research.elamur.ai/free/en/papers/wang-2024-math-shepherd-verify-reinforce-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiyi Wang, Lei Li, Zhihong Shao, et al.*2024 · 497 citations* - [DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence arXiv:2406.11931](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/) — DeepSeek-AI, Qihao Zhu, Daya Guo, et al. · 2024 · 196 citations - [DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search arXiv:2408.08152](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-v1-5-harnessing/) — Huajian Xin, Z. Z. Ren, Junxiao Song, et al. · 2024 · 116 citations - [DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data arXiv:2405.14333](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-advancing-theorem-proving/) — Huajian Xin, Daya Guo, Zhihong Shao, et al. · 2024 · 111 citations