$\textbf{Re}^{2}$: Unlocking LLM Reasoning via Reinforcement Learning with Re-solving
Pinzheng Wang · Shuli Xu · Juntao Li · Yu Luo · Dong Li · Jianye Hao · Min Zhang
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Pinzheng Wang · Shuli Xu · Juntao Li · Yu Luo · Dong Li · Jianye Hao · Min Zhang
Andrew Zhuoer Feng · Cunxiang Wang · Yu Luo · Lin Fan · Irene Zhou · Zikang Wang · Xiaotao Gu · Jie Tang · Hongning Wang · Minlie Huang
Evaluating the writing capabilities of large language models (LLMs) remains a significant challenge due to the multidimensional nature of writing skills and the limitations of existing metrics. LLM’s performance in thousand-words level and open-ended writing is inadequately assessed by traditiona...
Ruotao Xu · Yixin Ji · Yu Luo · Jinpeng Li · Dong Li · Peifeng Li · Juntao Li · Min Zhang
Large reasoning models (LRMs) have achieved strong performance enhancement through scaling test time computation, but due to the inherent limitations of the underlying language models, they still have shortcomings in tasks that require precise computation and extensive knowledge reserves. Tool-In...