SCI-PRM: A Tool Aware Process Reward Model for Scientific Reasoning Verification
While Process Reward Models (PRMs) have achieved remarkable success in mathematical reasoning, their application in complex scientific domains-such as biology, chemistry, and physics remains largely unexplored. Scientific problems demand not only logical rigor but also factual consistency and the precise usage of domain-specific tools, areas where current models often suffer from hallucinations and lack of verification. In this paper, we first construct SCIPRM70K, a large-scale dataset featuring Chain-of-Tool trajectories that explicitly interleave reasoning with the execution of scientific tools. Building upon this, we train an efficient reward model called Sci-PRM to provide fine-graine...
| Authors | Xiangyu Zhao, Henry Hengyuan Zhao, Yiheng Wang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 3 June 2026 |
| Last updated at source | 22 June 2026 |
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