#neural-network-robustness News & Analysis

2 articles tagged with #neural-network-robustness. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBearisharXiv – CS AI · May 77/10

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Sparse Tokens Suffice: Jailbreaking Audio Language Models via Token-Aware Gradient Optimization

Researchers demonstrate that audio language models can be jailbroken using sparse token optimization rather than dense waveform updates, with Token-Aware Gradient Optimization (TAGO) achieving comparable attack success rates while modifying only 25% of audio tokens. The findings reveal that gradient energy concentrates in specific audio regions, suggesting future AI safety research should account for this heterogeneous token-level structure.

AIBullisharXiv – CS AI · Mar 35/106

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Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection

Researchers propose PGOS (Policy-Guided Outlier Synthesis), a new framework that uses reinforcement learning to improve Graph Neural Network safety by better detecting out-of-distribution graphs. The system replaces static sampling methods with a learned exploration strategy that navigates low-density regions to generate pseudo-OOD graphs for enhanced detector training.