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arXiv · 2609.05807

MolParser-Mobile: Ultrafast OCSR System for Large-Scale Chemical Literature Mining

Xi Fang·Haocheng Lu·Han Lyu·Chengxiang Luo·Linfeng Zhang·Guolin Ke
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Abstract

Optical Chemical Structure Recognition (OCSR) is a fundamental component of chemical literature mining, enabling molecular database construction, reaction extraction, and AI-driven scientific discovery. Despite substantial progress in recognition accuracy with recent deep learning-based methods, inference throughput remains a critical bottleneck that limits web-scale deployment. To address this challenge, we propose MolParser-Mobile, an AutoML-optimized lightweight end-to-end OCSR framework. MolParser-Mobile contains only 9.98M parameters, while reaching a throughput of 1,520 molecules per second on a single NVIDIA RTX 4090D GPU. Despite its compact design, it maintains competitive and, on several benchmarks, superior recognition accuracy.

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Xi Fang, Haocheng Lu, Han Lyu, Chengxiang Luo, Linfeng Zhang, Guolin Ke. 2026-09-05. MolParser-Mobile: Ultrafast OCSR System for Large-Scale Chemical Literature Mining. https://arxiv.org/abs/2609.05807

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