# Transcribing Spanish Texts from the Past: Experiments with Transkribus, Tesseract and Granite

arXiv: https://arxiv.org/abs/2507.04878 · HTML: https://mlsanity.com/paper/2507.04878/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 20 references that are in the map.
- First posted on arXiv 7 Jul 2025.

## Builds on (most cited first, 4 of 4)

- [Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution](https://mlsanity.com/paper/2409.12191/) (2024)
- [olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models](https://mlsanity.com/paper/2502.18443/) (2025)
- [Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity Visual Descriptions](https://mlsanity.com/paper/2412.08737/) (2024)
- [Improving OCR Quality in 19th Century Historical Documents Using a Combined Machine Learning Based Approach](https://mlsanity.com/paper/2401.07787/) (2024)

## Built on by (most cited first, 1 of 1)

- [Pre-Editorial Normalization for Automatically Transcribed Medieval Manuscripts in Old French and Latin](https://mlsanity.com/paper/2602.13905/) (2026)

## Abstract (arXiv)

This article presents the experiments and results obtained by the GRESEL team in the IberLEF 2025 shared task PastReader: Transcribing Texts from the Past. Three types of experiments were conducted with the dual aim of participating in the task and enabling comparisons across different approaches. These included the use of a web-based OCR service, a traditional OCR engine, and a compact multimodal model. All experiments were run on consumer-grade hardware, which, despite lacking high-performance computing capacity, provided sufficient storage and stability. The results, while satisfactory, leave room for further improvement. Future work will focus on exploring new techniques and ideas using the Spanish-language dataset provided by the shared task, in collaboration with Biblioteca Nacional de Espa~na (BNE).