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Who cites «PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models»

54 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · ← back to «PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models»

  1. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
  2. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
  3. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
  4. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  5. 100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language ModelsarXiv:2505.00551Chong Zhang, Yue Deng, Xiang Lin, et al.2025 · 9 citations

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

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