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

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

HunyuanOCR-1.5 is a lightweight, end‑to‑end OCR‑specialized vision‑language model that unifies document parsing, text spotting, information extraction, text‑image translation, and multi‑image document understanding. It builds on the HunyuanOCR‑1.0 architecture, improving efficiency with DFlash‑based OCR decoding for faster inference (6.37× Transformer speedup, 2.14× under vLLM) and enhancing capability through an Agentic Data Flow system that autonomously constructs high‑quality training data for long‑tail OCR tasks. The model achieves top‑tier performance on OmniDocBench v1.6 and sets new milestones in ancient‑script OCR, chart/table parsing, multilingual parsing, and hallucination evaluation, while remaining lightweight for deployment.

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

We present HunyuanOCR-1. 5, a lightweight end-to-end OCR-specialized vision-language model.

Supercharge your OCR Pipelines with Open Models

DocOCR-Eval: A Correction-Based Framework for OCR Tool Selection Without Ground Truth

arXiv:2607. 16203v1 Announce Type: cross Abstract: Document parsing is a foundational step for document understanding tasks such as visual question answering and key information extraction, as it transforms unstructured scanned images into structured representations by extracting textual, visual, and layout information.

Finetuning olmOCR to be a faithful OCR-Engine

Parse Scanned PDFs for RAG with EasyOCR: Free OCR Gives You Words, Not a Document

Enterprise Document Intelligence [Vol. 1 #5quinquies] - Same 1974 scanned PDF, two engines.