AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work investigates prompt echoing small language models from different families and shows that echoing prompts are likely to have partial overlap with the training dataset but the phenomenon is primarily driven by the model's induction heads.
It is found that markets populated by LLM agents exhibit slower or no convergence towards market equilibrium, thus providing less efficient allocations than markets populated by humans, thus providing less efficient allocations than markets populated by humans.
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