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Towards Hierarchical Multi-Step Reward Models for Enhanced Reasoning in Large Language Models

arXiv — cs.CL•Tuesday, October 28, 2025 at 4:00:00 AM
NeutralArtificial Intelligence
Recent research highlights the challenges faced by Large Language Models (LLMs) in achieving reliable reasoning capabilities, particularly due to issues with the Process Reward Model (PRM) that can lead to reward hacking. This makes it difficult to identify the best intermediate steps in reasoning tasks. Additionally, the high cost of annotating reasoning processes for reward modeling poses a significant barrier to the large-scale collection of quality data. Understanding these limitations is crucial for advancing the development of more effective LLMs.
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