HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

arXiv:2607.04884 · cs.CV · Submitted 2026-07-06 · Read on arXiv

cs.CV

Submitted: 2026-07-06

Updated: 2026-09-17

Code: https://github.com/Tencent-Hunyuan/HunyuanOCR

Terminology

• Benchmark — 32× in this paper · explained in 2 episodes
• Transformer — 20× in this paper · explained in 2 episodes
• Reinforcement Learning — 17× in this paper · explained in 4 episodes
• Consistency — 16× in this paper · explained in 3 episodes
• Speculative Decoding — 13× in this paper · explained in 2 episodes
• Adam — 11× in this paper · explained in 2 episodes
• Verification — 11× in this paper · explained in 2 episodes
• Hallucination — 10× in this paper · explained in 3 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Actor — 8× in this paper · explained in 3 episodes
• Core — 8× in this paper · explained in 2 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Low-Resource Languages — 6× in this paper · explained in 4 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Benchmarking — 4× in this paper · explained in 3 episodes
• Evaluation Dimensions — 4× in this paper · explained in 3 episodes
• LLM-as-a-Judge — 4× in this paper · explained in 3 episodes
• Abundance — 3× in this paper · explained in 1 episode
• Robustness — 3× in this paper · explained in 5 episodes
• Adaptability — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Block Diffusion — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Agentic Flow — 1× in this paper · explained in 1 episode
• Agentic Task — 1× in this paper · explained in 1 episode
• Agentic Tasks — 1× in this paper · explained in 1 episode
• Annotation Errors — 1× in this paper · explained in 1 episode
• Average Precision — 1× in this paper
• Calibration — 1× in this paper · explained in 7 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multi-modal Inputs — 1× in this paper · explained in 2 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Structuring Chart-oriented Representation Metric — 1× in this paper
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Task Decomposition — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Tensor Parallelism — 1× in this paper
• Test-time Scaling — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• 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

• Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction
• Chronicles-OCR: A Cross-Temporal Perception Benchmark for the Evolutionary Trajectory of Chinese Characters
• ChartArena: Benchmarking Chart Parsing across Languages, Scenarios, and Formats
• GPT-4o System Card
• Gemini: A Family of Highly Capable Multimodal Models
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• Qwen2.5-VL Technical Report
• Qwen3-VL Technical Report
• Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
• Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
• InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• HunyuanOCR Technical Report
• MinerU-Diffusion: Rethinking Document OCR as Inverse Rendering via Diffusion Decoding
• DFlash: Block Diffusion for Flash Speculative Decoding
• Fast-dLLM v2: Efficient Block-Diffusion LLM
• AgentInstruct: Toward Generative Teaching with Agentic Flows

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