AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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FireWorldBench evaluates whether models can infer latent physical states, explain underlying mechanisms, forecast coupled-field evolution, and assess intervention consequences from multimodal partial observations, providing a challenging testbed for complex physical world intelligence.
SEBA is a sample-efficient framework for black-box adversarial attacks on visual RL agents that significantly reduces cumulative rewards, preserves visual fidelity, and greatly decreases environment interactions compared to prior black-box and white-box methods.
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