AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Agent harnesses specify the roles, instructions, tools, and communication structure used to solve a task, and the right harness depends on the query. Because the value of each design choice is observable only through execution, tailoring a harness to each query has required either executing alternatives at inference ti...
Reliable video world models could provide scalable predictive environments for robot learning, planning, and evaluation. However, generated robot videos can violate physical principles and complete tasks through physically implausible behavior, limiting their reliability for robot learning and planning. Current video-g...
ARC (Agentic Resource&Configuration learner), a lightweight hierarchical policy that dynamically selects query-specific agent configurations, consistently improves over budget-matched tool-augmented LLMs, demonstrating that learning per-query agent configurations is a powerful alternative to"one size fits all"designs.
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