AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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CAKE, a compiler-agent co-design in which agents author CAKE IR, a typed, hardware-explicit schedule representation, exposes warp roles, memory movement, synchronization, and pipelines while supporting verification, cost modeling, and localized diagnostics.
Together, these results support multi-view repository-context serving with explicit, operation-specific validity boundaries with quality-cost frontiers across the repository-context lifecycle.
CHORUS is presented, a post-training framework that pushes performance beyond what a conventional supervised fine-tuning (SFT)-to-reinforcement learning (RL) pipeline achieves, and consolidates the resulting specialists into a single 4B model.
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