FocusVTC: Efficient and High-Performance Visual Text Compression with Adaptive Resolution

arXiv:2609.36651 · cs.CV, cs.AI · Submitted 2026-09-29 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• GRPO — 48× in this paper · explained in 6 episodes
• Benchmark — 17× in this paper · explained in 2 episodes
• Trace — 10× in this paper · explained in 2 episodes
• Adam — 8× in this paper · explained in 2 episodes
• Fine-Tuning — 7× in this paper · explained in 5 episodes
• Reasoning Traces — 5× in this paper · explained in 3 episodes
• Group Relative Policy Optimization — 4× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• Fidelity — 3× in this paper · explained in 2 episodes
• Grounding — 3× in this paper · explained in 3 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Vision-language models — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Distillation — 2× in this paper · explained in 2 episodes
• RAG — 2× in this paper · explained in 3 episodes
• Sparse Attention — 2× in this paper · explained in 5 episodes
• Two-stage training — 2× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• GRPO Objective — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Group Relative Policy Optimization (GRPO) — 1× in this paper · explained in 5 episodes
• KV cache — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Thinking mode — 1× in this paper · explained in 2 episodes
• Verification — 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
• Reading is not Reasoning: Bridging the Agentic Policy Gap in Vision-Text Compression
• Decoupling semantics from vision: A framework for faithful visual-text compression evaluation
• The Llama 3 Herd of Models
• Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression
• ChatQA: Surpassing GPT-4 on Conversational QA and RAG
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Visual Text Compression as Measure Transport
• Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries
• VTC-R1: Vision-Text Compression for Efficient Long-Context Reasoning
• DeepSeek-OCR: Contexts Optical Compression
• ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
• Qwen3 Technical Report
• Magnifying What Matters: Attention-Guided Adaptive Rendering for Visual Text Comprehension

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