Xiaomi-OCR-0 Technical Report

arXiv:2609.36136 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/datalab-to/marker

Terminology

• Benchmark — 20× in this paper · explained in 2 episodes
• Verification — 14× in this paper · explained in 2 episodes
• Consistency — 11× in this paper · explained in 3 episodes
• Ablation — 9× in this paper · explained in 1 episode
• Self-consistency — 9× in this paper · explained in 2 episodes
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Robustness — 6× in this paper · explained in 5 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Ensemble Triplet Consensus — 3× in this paper
• Synthetic Data Generation — 3× in this paper · explained in 5 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• On-Policy Distillation — 2× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 1× in this paper
• Character Detection Matching — 1× in this paper
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Optical Character Recognition — 1× in this paper
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Synthetic Data Generation Pipeline — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Tree-Edit-Distance-based Similarity — 1× in this paper
• Unified Framework — 1× in this paper · explained in 5 episodes
• Verifiable Rewards — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• Qwen3-VL Technical Report
• Qwen2.5-VL Technical Report
• Seed1.8 Model Card: Towards Generalized Real-World Agency
• Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• Youtu-Parsing: Perception, Structuring and Recognition via High-Parallelism Decoding
• Logics-Parsing Technical Report
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model
• PaddleOCR 3.0 Technical Report
• RT-DocLayout: Real-Time End-to-End Document Layout Analysis with Reading Order in the Wild
• PaddleOCR-VL-1.5: Towards a Multi-Task 0.9B VLM for Robust In-the-Wild Document Parsing
• Qianfan-OCR: A Unified End-to-End Model for Document Intelligence
• UniRec-0.1B: Unified Text and Formula Recognition with 0.1B Parameters
• GLM-OCR Technical Report
• Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting
• Dolphin-v2: Universal Document Parsing via Scalable Anchor Prompting
• Mini-Monkey: Alleviating the Semantic Sawtooth Effect for Lightweight MLLMs via Complementary Image Pyramid
• HunyuanOCR Technical Report
• ABot-OCR Technical Report

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• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models