document-understanding

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

Parsing-free RAG supported by VLMs

Code for the paper "PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks" (ICPR 2020)

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.

A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating.

Minimal sharded dataset loaders, decoders, and utils for multi-modal document, image, and text datasets.

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