--- title: "Who cites DeepSeekMath-V2: Towards — 32 citing papers" description: "32 papers of the Elamur Research library cite «DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning», found in their…" canonical: "https://research.elamur.ai/free/en/papers/shao-2025-deepseekmath-v2-self-verifiable/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/shao-2025-deepseekmath-v2-self-verifiable/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [DeepSeekMath-V2: Towards Self-Verifiable…](https://md.research.elamur.ai/free/en/papers/shao-2025-deepseekmath-v2-self-verifiable/) / cited by # Who cites «DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning» 32 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning»](https://md.research.elamur.ai/free/en/papers/shao-2025-deepseekmath-v2-self-verifiable/) 1. [**DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models arXiv:2512.02556**DeepSeek-AI, Aixin Liu, Aoxue Mei, et al.*2025 · 341 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-v3-2-pushing/) 2. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arXiv:2606.19348**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 122 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/) 3. [**Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from Experience arXiv:2512.17260**Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-seed-prover-1-5/) 4. [**Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation arXiv:2603.19220**Zhuolin Yang, Zihan Liu, Yang Chen, et al.*2026 · 16 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-nemotron-cascade-2-post-training/) 5. **[Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/wang-2026-learning-while-staying-curious-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Wang, Hao Gu, Hongming Piao, et al.*2026 · 3 citations* 6. **[Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward Models](https://md.research.elamur.ai/free/en/papers/wang-2026-outcome-accuracy-is-not-enough/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binghai Wang, Yantao Liu, Yuxuan Liu, et al.*2026 · 3 citations* 7. **[Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math](https://md.research.elamur.ai/free/en/papers/pandit-2026-hard2verify-step-level-verification-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shrey Pandit, Austin Xu, Xuan-Phi Nguyen, et al.*2026 · 2 citations* 8. **[AgentV-RL: Scaling Reward Modeling with Agentic Verifier](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentv-rl-scaling-reward-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiazheng Zhang, Ziche Fu, Zhiheng Xi, et al.*2026* 9. **[Chaining the Evidence: Robust Reinforcement Learning for Deep Search Agents with Citation-Aware Rubric Rewards](https://md.research.elamur.ai/free/en/papers/zhang-2026-chaining-evidence-robust-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajie Zhang, Xin Lv, Ling Feng, et al.*2026* 10. **[Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-distributional-clarity-hidden-driver-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaoning Sun, Mingzhu Cai, Huang He, et al.*2026* 11. **[Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale](https://md.research.elamur.ai/free/en/papers/tu-2026-fico-evaluating-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.*2026* 12. **[ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction Following](https://md.research.elamur.ai/free/en/papers/yang-2026-imprif-stronger-implicit-reasoning-leads/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuancheng Yang, Lin Yang, Xu Wang, et al.*2026* 13. **[RADO: Reasoning Audit-Driven Optimization for Rigorous Reasoning in High-Stakes Domains](https://md.research.elamur.ai/free/en/papers/tan-2026-rado-reasoning-audit-driven-optimization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijie Tan, Xu Chu, Guanyu Wang, et al.*2026* 19 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/shao-2025-deepseekmath-v2-self-verifiable/) — DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning