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Is PRM Necessary? Problem-Solving RL Implicitly Induces PRM Capability in LLMs

arXiv — cs.LG•Tuesday, December 9, 2025 at 5:00:00 AM
NeutralArtificial Intelligence
  • Recent research indicates that large language models (LLMs) can enhance their reasoning capabilities through pure reinforcement learning (RL) focused on problem-solving, without the need for process reward models (PRMs). This finding challenges the traditional belief that PRMs are essential for developing reasoning skills in LLMs, as demonstrated by the DeepSeek-R1 model.
  • The implications of this research are significant for the field of artificial intelligence, as it suggests that LLMs can achieve advanced reasoning abilities through RL alone, potentially reducing the reliance on complex supervisory frameworks like PRMs.
  • This development aligns with ongoing discussions in AI research regarding the balance between different training methodologies, such as RL and process supervision, and highlights the importance of optimizing reasoning capabilities while addressing challenges like overthinking and redundancy in reasoning processes.
— via World Pulse Now AI Editorial System
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