AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work examines what structure is supplied by the game or workflow, what AI learns or produces, which capabilities and artifacts transfer across settings and roles, and what evidence supports the claims and identifies cross-role connections.
MineExplorer benchmark for evaluating open-world exploration capabilities of MLLM agents in Minecraft is introduced, which first filter atomic tasks whose solutions rely heavily on Minecraft-specific knowledge to better reflect general open-world reasoning and compose atomic tasks into implicit multi-hop tasks.
Results validate that a lightweight inference-time intervention can substantially boost GUI Agent's competence to identify inappropriate execution scenarios and refrain from unnecessary actions.
Persuasion Duality is identified: reasoning enhances an agent's persuasive power while simultaneously increasing its resistance to persuasion, and a prompt-level adversarial argument detection method is proposed that consistently improves agent robustness.
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