LOCA-R: Near-Perfect Performance on the Chinese Physics Olympiad 2025
Authors
Dong-Shan Jian
Xiang Li
Chen-Xu Yan
Hui-Wen Zheng
Zhi-Zhang Bian
You-Le Fang
Sheng-Qi Zhang
Bing-Rui Gong
Ren-Xi He
Jing-Tian Zhang
Ce Meng
Yan-Qing Ma
Abstract
Olympiad-level physics problem-solving presents a significant challenge for both humans and artificial intelligence (AI), as it requires a sophisticated integration of precise calculation, abstract reasoning, and a fundamental grasp of physical principles. The Chinese Physics Olympiad (CPhO), renowned for its complexity and depth, serves as an ideal and rigorous testbed for these advanced capabilities. In this paper, we introduce LOCA-R (LOgical Chain Augmentation for Reasoning), an improved version of the LOCA framework adapted for complex reasoning, and apply it to the CPhO 2025 theory examination. LOCA-R achieves a near-perfect score of 313 out of 320 points, solidly surpassing the highest-scoring human competitor and significantly outperforming all baseline methods.
