When Scene Text Hijacks the Scene: Uncovering, Exploiting, and Mitigating Rendered-Text Semantic Leakage in Image Generation Models

arXiv:2610.11286 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Code: https://github.com/llffff/rendertext

Terminology

• Benchmark — 20× in this paper · explained in 2 episodes
• Diffusion Model — 16× in this paper · explained in 8 episodes
• Fidelity — 16× in this paper · explained in 2 episodes
• Diffusion Models — 15× in this paper · explained in 6 episodes
• Alignment — 12× in this paper · explained in 1 episode
• Ablation — 9× in this paper · explained in 1 episode
• Transformer — 8× in this paper · explained in 2 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Grounding — 3× in this paper · explained in 3 episodes
• Latent Diffusion Model — 3× in this paper · explained in 2 episodes
• Latent Diffusion Models — 3× in this paper · explained in 2 episodes
• Semantic Alignment — 3× in this paper · explained in 3 episodes
• Verifier — 3× in this paper · explained in 2 episodes
• Accountability — 2× in this paper · explained in 2 episodes
• Agentic Loop — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• IEEE Symposium on Security and Privacy — 2× in this paper
• Steering — 2× in this paper · explained in 2 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Alignment Techniques — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer
• Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
• Emerging Properties in Unified Multimodal Pretraining
• PP-OCR: A Practical Ultra Lightweight OCR System
• ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
• LlavaGuard: An Open VLM-based Framework for Safeguarding Vision Datasets and Models
• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
• Image Can Bring Your Memory Back: A Novel Multi-Modal Guided Attack against Image Generation Model Unlearning
• SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
• UnsafeBench: Benchmarking Image Safety Classifiers on Real-World and AI-Generated Images
• Hierarchical Text-Conditional Image Generation with CLIP Latents
• LongCat-Image Technical Report
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• Qwen-Image Technical Report
• Seeing Is No Longer Believing: Frontier Image Generation Models, Synthetic Visual Evidence, and Real-World Risk
• OCRGenBench: A Comprehensive Benchmark for Evaluating OCR Generative Capabilities
• When Memory Becomes a Vulnerability: Towards Multi-turn Jailbreak Attacks against Text-to-Image Generation Systems

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