Introducing Mistral OCR 3

Mistral OCR

Introducing Mistral OCR 4

Mistral OCR 4 delivers enterprise document AI with 170-language support, bounding boxes, and self-hosted deployment.

Finetuning olmOCR to be a faithful OCR-Engine

SOTA OCR with Core ML and dots.ocr

Introducing Mistral 3

ClinOCR-Bench: A Comprehensive Clinical Scanned Document Dataset for Optical Character Recognition Model Evaluation

arXiv:2607. 03650v1 Announce Type: cross Abstract: Extracting textual information from scanned medical documents, such as external laboratory reports and manually filled forms, has been a major challenge in modern electronic health records (EHRs).

Supercharge your OCR Pipelines with Open Models

Color Independent Word Segmentation From Transcribed Bangla Passages

The paper presents a color‑independent word segmentation method for handwritten Bangla text images. It works on smartphone‑captured images regardless of paper color or ink type, and the custom dataset includes various real‑world challenges such as shadows. The system achieves 90.60 % recall, 91.80 % precision, and 91.20 % F1‑score on 7,374 words.

PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters

Introducing Mistral Code

When Do VLMs Help Arabic Manuscript OCR? A Cross-Dataset Study

arXiv:2608.22366v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being used for document understanding, yet their role in Arabic and Islamic manuscript recognition remai...

PaddleOCR 3.5: Running OCR and Document Parsing Tasks with a Transformers Backend