🧑‍🔬 Who cites Jiewen Hu

50 citations of their works from 50 papers of our library (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · ← Jiewen Hu

1. DeepSeek-V3.2: Pushing the Frontier of Open Large Language ModelsarXiv:2512.02556DeepSeek-AI, Aixin Liu, Aoxue Mei, et al.2025 · 341 citations
2. DeepSeek-V4: Towards Highly Efficient Million-Token Context IntelligencearXiv:2606.19348DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.2026 · 122 citations
3. DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree SearcharXiv:2408.08152Huajian Xin, Z. Z. Ren, Junxiao Song, et al.2024 · 116 citations
4. Formal Mathematical Reasoning: A New Frontier in AIarXiv:2412.16075Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.2024 · 49 citations
5. Seed-Prover: Deep and Broad Reasoning for Automated Theorem ProvingarXiv:2507.23726Luoxin Chen, Jinming Gu, Liankai Huang, et al.2025 · 46 citations
6. Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from ExperiencearXiv:2512.17260Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.2025 · 19 citations
7. APOLLO: Automated LLM and Lean Collaboration for Advanced Formal ReasoningConference on Neural Information Processing Systems (NeurIPS)Azim Ospanov, Farzan Farnia, Roozbeh Yousefzadeh2025 · 17 citations
8. Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy DistillationarXiv:2603.19220Zhuolin Yang, Zihan Liu, Yang Chen, et al.2026 · 16 citations
9. Rewarding the Unlikely: Lifting GRPO Beyond Distribution SharpeningConference on Empirical Methods in Natural Language Processing (EMNLP)Andre Wang He, Daniel Fried, Sean Welleck2025 · 15 citations
10. Mathematical Proof as a Litmus Test: Revealing Failure Modes of Advanced Large Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Dadi Guo, Jiayu Liu, Zhiyuan Fan, et al.2026 · 5 citations
11. Premise Selection for a Lean HammerarXiv:2506.07477Thomas Zhu, Joshua Clune, Jeremy Avigad, et al.2025 · 5 citations
12. ImProver: Agent-Based Automated Proof OptimizationarXiv:2410.04753Riyaz Ahuja, Jeremy Avigad, Prasad Tetali, et al.2024 · 5 citations
13. miniF2F-Lean Revisited: Reviewing Limitations and Charting a Path ForwardConference on Neural Information Processing Systems (NeurIPS)Azim Ospanov, Farzan Farnia, Roozbeh Yousefzadeh2025 · 4 citations
14. Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Wang, Hao Gu, Hongming Piao, et al.2026 · 3 citations
15. Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Binghai Wang, Yantao Liu, Yuxuan Liu, et al.2026 · 3 citations
16. Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier MathAnnual Meeting of the Association for Computational Linguistics (ACL)Shrey Pandit, Austin Xu, Xuan-Phi Nguyen, et al.2026 · 2 citations
17. AgentV-RL: Scaling Reward Modeling with Agentic VerifierFindings of the Association for Computational LinguisticsJiazheng Zhang, Ziche Fu, Zhiheng Xi, et al.2026
18. Chaining the Evidence: Robust Reinforcement Learning for Deep Search Agents with Citation-Aware Rubric RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Jiajie Zhang, Xin Lv, Ling Feng, et al.2026
19. Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Shaoning Sun, Mingzhu Cai, Huang He, et al.2026
20. Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at ScaleFindings of the Association for Computational LinguisticsJianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.2026
21. ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction FollowingAnnual Meeting of the Association for Computational Linguistics (ACL)Yuancheng Yang, Lin Yang, Xu Wang, et al.2026
22. RADO: Reasoning Audit-Driven Optimization for Rigorous Reasoning in High-Stakes DomainsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhijie Tan, Xu Chu, Guanyu Wang, et al.2026

28 more citing papers of our library have no page here yet.

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