y0news
← Feed
Back to feed
🧠 AI🔴 BearishImportance 7/10

Multi-PA: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models

arXiv – CS AI|Jie Zhang, Xiangkui Cao, Zhouyu Han, Shiguang Shan, Xilin Chen||3 views
🤖AI Summary

Researchers introduce Multi-PA, a comprehensive benchmark for evaluating privacy risks in Large Vision-Language Models (LVLMs), covering 26 personal privacy categories, 15 trade secrets, and 18 state secrets across 31,962 samples. Testing 21 open-source and 2 closed-source LVLMs revealed significant privacy vulnerabilities, with models generally posing high risks of facilitating privacy breaches across different privacy categories.

Key Takeaways
  • Multi-PA benchmark evaluates LVLMs across two dimensions: privacy awareness and privacy leakage risks.
  • The benchmark covers 59 total privacy categories with over 31,000 test samples spanning personal, trade, and state secrets.
  • Testing of 23 LVLMs revealed generally high risks of privacy breaches across all models evaluated.
  • Current LVLMs show varying vulnerabilities across different types of sensitive information categories.
  • The research highlights significant privacy limitations that could restrict practical applications of LVLMs.
Read Original →via arXiv – CS AI
Act on this with AI
Stay ahead of the market.
Connect your wallet to an AI agent. It reads balances, proposes swaps and bridges across 15 chains — you keep full control of your keys.
Connect Wallet to AI →How it works
Related Articles