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CVPR 2026

MCHDoc: A Comprehensive Benchmark for Reading Multi-Carrier Chinese Historical Documents

Yijun Sheng, Shipeng Zhu, Ruijia Zuo, Na Nie, Hui Xue

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摘要

Reading Chinese historical documents across diverse carriers is central to understanding the evolution of Chinese civilization, yet remains labor-intensive and dependent on scarce expert knowledge. Although recent large-scale models show promise on isolated historical collections, they do not systematically probe the fundamental ability to read historical documents across heterogeneous carriers. Therefore, we present MCHDoc, a comprehensive benchmark for reading multi-carrier Chinese historical documents. MCHDoc spans over 3,000 years of history and contains 15,724 high-resolution documents from six major carriers, capturing rich variations in material, layout, etc. Mimicking expert workflows, the benchmark supports page-level and character-level recognition, as well as LLM-based post-correction with and without external knowledge. We systematically evaluate a wide range of large-scale models on MCHDoc. The results show that even top-tier models struggle with multi-carrier historical documents. Furthermore, our analysis highlights several key factors for effectively adapting large models to Chinese historical texts. MCHDoc thus offers a standardized, challenging, and historically grounded benchmark for reading Chinese historical documents and provides a foundation for future research in document analysis and digital humanities.