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English Information

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Authors
# Name
1 Renato Miyaji(re.miyaji@usp.br)
2 Arthur Luz(athomasluz@gmail.com)
3 Renato Moulin(renato.moulin@visagio.com)
4 Leonardo Machado(leonardo.machado@visagio.com)
5 Pedro Corrêa(pedro.correa@usp.br)

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Reference
# Reference
1 An, Z., Ding, X., Fu, Y.-C., Chu, C.-C., Li, Y., and Du, W. (2024). Golden-retriever: High-fidelity agentic retrieval augmented generation for industrial knowledge base. arXiv preprint arXiv:2408.00798.
2 DeepMind, G. (2025a). Gemini 3 flash: Frontier intelligence built for speed. https: //blog.google/products/gemini/gemini-3-flash.
3 DeepMind, G. (2025b). Gemini 3 pro: State-of-the-art multimodal ai model. https: //blog.google/products/gemini/gemini-3.
4 Gao, S., Zhao, S., Jiang, X., Duan, L., Chng, Y. X., Chen, Q.-G., Luo, W., Zhang, K., Bian, J.-W., and Gong, M. (2025). Scaling beyond context: A survey of multimo- dal retrieval-augmented generation for document understanding. arXiv preprint ar- Xiv:2510.15253.
5 Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., and Wang, H. (2023). Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv:2312.10997.
6 Gu, J., Kuen, J., Morariu, V. I., Zhao, H., Barmpalios, N., Jain, R., Nenkova, A., and Sun, T. (2021). Unified pretraining framework for document understanding. In Advances in Neural Information Processing Systems (NeurIPS 2021).
7 Kim, G., Hong, T., Yim, M., Nam, J., Park, J., Yim, J., Hwang, W., Yun, S., Han, D., and Park, S. (2022). Ocr-free document understanding transformer. In Proceedings of the 17th European Conference on Computer Vision (ECCV 2022), pages 498–517, Berlin, Heidelberg. Springer-Verlag.
8 Mandal, S., Talewar, A., Ahuja, P., and Juvatkar, P. (2025). Nanonets-ocr-s: A mo- del for transforming documents into structured markdown with intelligent content recognition and semantic tagging. https://huggingface.co/nanonets/ Nanonets-OCR-s
9 McKie, J. X. (2024). PyMuPDF: Python bindings for the MuPDF library. Version 1.24.x
10 Mei, L., Mo, S., Yang, Z., and Chen, C. (2025). A survey of multimodal retrieval- augmented generation. arXiv preprint arXiv:2504.08748.
11 Qwen (2025). Qwen2.5-vl-3b: Instruction-tuned vision-language model. https:// huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct
12 Xu, Y., Li, M., Cui, L., Huang, S., Wei, F., and Zhou, M. (2020). Layoutlm: Pre-training of text and layout for document image understanding. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD ’20, pages 1192–1200, New York, NY, USA. Association for Computing Machinery