AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper proposes a novel Large Language Model (LLM)-driven Training-free Automatic Proxy (dubbed TAP) discovery framework that reforms the design paradigm of MPQ by utilizing LLMs and evolutionary search strategies to automatically find superior TAP tailored for MPQ.
RSRA is proposed, a training-free rank allocator that estimates where adaptation capacity is most needed through forward-only representation sensitivity probing on a small calibration set and achieves the highest average performance in all three reported model-benchmark settings and a 1.93x speedup in allocation time o...
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