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A single unified model can outperform specialized systems across various computer vision tasks, all without the need for custom architectures.
SpikeTimer achieves a remarkable balance between copyright protection and performance, maintaining high accuracy on authorized data while effectively misclassifying unauthorized inputs.
LLM defenses can achieve a 79% reduction in attack success rate against evolving multi-round attacks by using a stateful, multi-agent cooperative framework.
Semantic disagreement between LLMs reveals crucial uncertainty that single-model metrics miss, and Collaborative Entropy (CoE) captures it.
