AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Large language models (LLMs) excel across diverse tasks, benefiting from knowledge priors, in-context reasoning, and test-time computation. Despite these strengths, single-model reasoning remains vulnerable to error propagation, as later steps depend on the model's earlier outputs, leaving reasoning blind spots difficu...
Prompt tuning offers an efficient way to adapt frozen vision-language models to unsupervised domain adaptation (UDA). Existing prompt-based UDA methods usually rely on domain-aware prompts, but they often couple category semantics and domain correction throughout the prompt hierarchy. This coupling can introduce redund...
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