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The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. This repository is actively maintained, and new features are continuously being added.

License: MIT License

Python 96.12% CSS 0.44% Dockerfile 2.95% Shell 0.50%
biases layoutlm layoutlmv2 layoutlmv3 layoutxlm llms-benchmarking synthetic-dataset synthetic-dataset-generation token-classification

merit-dataset's Introduction

Hi there! ๐Ÿ‘‹

About me ๐Ÿ‘จโ€๐Ÿ’ป

I am Nacho de Rodrigo, a PhD student at the Institute for Research in Engineering. My PhD topic is synthetic image generation, which involves generating images in controlled environments to obtain multimodal datasets. With these datasets, I can train Deep Learning Models and solve problems where data is scarce, detect biases in Large Language Models, or provide deeper explainability for AI.

Here you can find an example from my last research project: the MERIT-Dataset

Blender Cloth Simulation

Teaching/Supervising ๐Ÿ‘จโ€๐Ÿซ

I am an active member at Comillas-ICAI University, working with undergrad students on different topics:

  • ๐Ÿ“š I teach laboratory sessions on Introduction to Computer Vision. You can find some of my student's projects here:
  • ๐Ÿ‘€ I supervise scholarships and bachelor/master's theses. You can find some of the projects I have supervised here:
    • A dataset and fine-tuned LLM to summarize phone calls: Call-Sum
    • A tangible user interface to simulate mobility flows in cities: Bord
    • A plug-and-play Augmented Reality library for Python: Armor

ARMOR BORD

merit-dataset's People

Contributors

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Forkers

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