Stealth Fine-Tuning: Efficiently Breaking Alignment in RVLMs Using Self-Generated CoT
Published:Nov 18, 2025 03:45
•1 min read
•ArXiv
Analysis
This article likely discusses a novel method for manipulating or misaligning Robust Vision-Language Models (RVLMs). The use of "Stealth Fine-Tuning" suggests a subtle and potentially undetectable approach. The core technique involves using self-generated Chain-of-Thought (CoT) prompting, which implies the model is being trained to generate its own reasoning processes to achieve the desired misalignment. The focus on efficiency suggests the method is computationally optimized.
Key Takeaways
Reference
“The article's abstract or introduction would likely contain a more specific definition of "Stealth Fine-Tuning" and explain the mechanism of self-generated CoT in detail.”