AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Memory Adaptation for Task-Conditioned Execution (MATE) is introduced, a deterministic post-retrieval procedure that converts trajectories into execution-oriented memory and supports memory adaptation as a distinct stage between retrieval and embodied execution.
This work proposes NOSA, a trainable sparse attention mechanism natively designed for KV cache offloading that explicitly constrains the volume of CPU-GPU KV transfers, thereby achieving low communication overhead and high decoding throughput.
FutureBridge is presented, which ranks joint LLM-SLM token candidates according to how well they support the SLM's subsequent reasoning, and indicates that token selection benefits from modeling whether the receiving SLM can use each candidate to continue reasoning, rather than relying on the LLM's local preference alo...
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