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layoutlmv3

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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.

  • Updated Jul 16, 2025
  • Python
cheque-verification-layoutllm

End-to-end computer vision + NLP system for automated bank cheque verification — LayoutLMv3 encoder fused with a LoRA fine-tuned TinyLlama decoder to extract payee, amounts, date & signature as structured JSON, with automated fraud checks and a Streamlit demo.

  • Updated Jul 4, 2026
  • Jupyter Notebook

Privacy-first financial document processing engine for invoices, receipts, and expense vouchers. Combines Tesseract OCR, spatial token alignment, deterministic financial validation, human-in-the-loop review, and optional LayoutLMv3 for local document extraction.

  • Updated Sep 24, 2026
  • Python

Intelligent Document Processing: LayoutLMv3 fine-tuning (PyTorch) alongside rule, LLM and transformer QA backends, with OCR, Swiss validation (IBAN/MWST), human-in-the-loop review, MLflow, Prometheus and Kubernetes.

  • Updated Sep 4, 2026
  • Python

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