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Chenlong Deng · Mengjie Deng · Junjie Wu · Dun Zeng · Teng Wang · Qingsong Xie · Jiadeng Huang · Shengjie Ma · Changwang Zhang · Zhaoxiang Wang · Jun Wang · Yutao Zhu · Zhicheng Dou
Teng Wang · Jiang Zhangyi · Zhenqi He · Hailei Gong · Shenyang Tong · Wenhan Yang · Zeyu Li · Yanan Zheng · Zifan He · Zewen Ye · Shengjie Ma · Jianping Zhang
Large Language Models (LLMs) have demonstrated strong mathematical reasoning abilities through supervised fine-tuning and reinforcement learning. However, existing Process Reward Models (PRMs) are vulnerable to reward hacking and require expensive, large-scale annotation of reasoning steps, limit...
Zhichao Shi · Xuhui Jiang · Chengjin Xu · Cangli Yao · Shengjie Ma · Yinghan Shen · Zixuan Li · Jian Guo · Yuanzhuo Wang
Current evaluation methods for large language models (LLMs) primarily rely on static benchmarks, presenting two major challenges: limited knowledge coverage and fixed difficulties that mismatch with the evaluated LLMs. These limitations lead to superficial assessments of LLM knowledge, thereby im...