Chu, Pei

OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations

Ouyang, L., Qu, Y., Zhou, H., Zhu, J., Zhang, R., Lin, Q., Wang, B., Zhao, Z., Jiang, M., Zhao, X., et al. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Handwritten Text Recognition TechniquesInformation Systems and Technology Applications

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OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations

Ouyang, L., Qu, Y., Zhou, H., Zhu, J., Zhang, R., Lin, Q., Wang, B., Zhao, Z., Jiang, M., Zhao, X., et al. (2024) · arXiv

Handwritten Text Recognition TechniquesInformation Systems and Technology Applications

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InternLM2 Technical Report

Cai, Z., Cao, M., Chen, H., Chen, K., Chen, K., Chen, X., Chen, X., Chen, Z., Chen, Z., Chu, P., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

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MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing

Niu, J., Liu, Z., Gu, Z., Wang, B., Ouyang, L., Zhao, Z., Chu, T., He, T., Wu, F., Zhang, Q., et al. (2025) · arXiv

Handwritten Text Recognition TechniquesAdvanced Neural Network Applications

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