#alignment-paradox News & Analysis

2 articles tagged with #alignment-paradox. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBearisharXiv – CS AI · Jun 57/10

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Safety Paradox: How Enhanced Safety Awareness Leaves LLMs Vulnerable to Posterior Attack

Researchers have discovered a critical vulnerability in safety-aligned large language models called Posterior Attack, which exploits the very safety mechanisms designed to prevent harmful outputs. The attack works by prompting models to generate responses their internal classifiers would flag as unsafe, and paradoxically, more sophisticated safety-aligned models are more vulnerable to this exploitation than less-aligned ones.

🧠 GPT-5🧠 Claude

AIBearisharXiv – CS AI · May 277/10

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A Universal Cliff and a Design Fingerprint: Cross-Section Defect Detection Under LLM Orchestration

Researchers discovered that large language models fail catastrophically at detecting contradictions spanning multiple sections of documents when using multi-agent orchestration systems, despite performing well in single-agent scenarios. The detection failure is universal across model families and generations, and alignment improvements don't fix the structural problem—creating a critical vulnerability in production LLM systems.