MAD-Guard: Controlled Study of Autoregressive Generation versus Direct Decision Interfaces for Closed Multimodal Forensic Tasks

arXiv:2609.33683 · cs.CV, cs.CR · Submitted 2026-09-27 · Read on arXiv

cs.CV, cs.CR

Submitted: 2026-09-27

Updated: 2026-09-27

Code: https://github.com/moyuan10086/MAD-Guard

Terminology

• Accuracy — 29× in this paper · explained in 1 episode
• AUC — 24× in this paper · explained in 2 episodes
• Calibration — 12× in this paper · explained in 7 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• Foundation Model — 4× in this paper · explained in 3 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Adaptation — 3× in this paper · explained in 1 episode
• Generalization — 3× in this paper · explained in 13 episodes
• Tokenization — 3× in this paper · explained in 2 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• International Conference on Computer Vision — 2× in this paper
• LoRA Adapters — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Structured Reasoning — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Vision-language models — 2× in this paper · explained in 2 episodes
• Agentic Workflows — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Embeddings — 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
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Hamming Distance — 1× in this paper · explained in 2 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 1× in this paper
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Deep Residual Injection for Full-Spectrum Forensic Signal Perception in Multimodal Large Language Models
• PRPO: Paragraph-level Policy Optimization for Vision-Language Deepfake Detection
• VIGIL: Part-Grounded Structured Reasoning for Generalizable Deepfake Detection
• FakeVLM-R1: Internalizing Physical Laws via CoT for Synthetic Image Detection
• Perception, Verdict, and Evolution: Hindsight-Driven Self-Refining Forensics Agent for AI-Generated Image Detection
• Evidence-Grounded Forensic Reasoning for Detecting and Grounding Multi-Modal Media Manipulation
• 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
• GLiNER Guard: Unified Encoder Family for Production LLM Safety and Privacy
• SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning
• Training Deep Nets with Sublinear Memory Cost

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