RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
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Updated
Dec 24, 2024 - Python
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
A Repo For Document AI
mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding
A collection of original, innovative ideas and algorithms towards Advanced Literate Machinery. This project is maintained by the OCR Team in the Language Technology Lab, Tongyi Lab, Alibaba Group.
A curated list of resources for Document Understanding (DU) topic
Code for the paper "PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks" (ICPR 2020)
Parsing-free RAG supported by VLMs
Official PyTorch implementation of LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding (ACL 2022)
Sample applications and demos for Document AI, the end-to-end document processing platform on Google Cloud
Algorithms, papers, datasets, performance comparisons for Document AI. Continuously updating.
Minimal sharded dataset loaders, decoders, and utils for multi-modal document, image, and text datasets.
A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating.
DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Models
Doc2Graph transforms documents into graphs and exploit a GNN to solve several tasks.
ReadingBank: A Benchmark Dataset for Reading Order Detection
Object Detection Model for Scanned Documents
Checkbox Detection Model for Scanned Documents
Datasets and Evaluation Scripts for CompHRDoc
[MM'2024] PEneo, an effective algorithm for key-value pair extraction from form-like documents, designed for real-world applications.
TAT-DQA: Towards Complex Document Understanding By Discrete Reasoning
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