AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work reviews 28 papers posted between 19 and 24 September and relates their findings to earlier work on label-probability classification, constrained decoding, reranking, calibration, and model cascades and uses recurring weaknesses in these studies to derive a 14-item evaluation checklist for future TDM work.
It is shown that measured outcomes can depend on the serving layer rather than model behavior alone rather than model behavior alone, and a checklist for treating serving behavior as part of the evaluation protocol is concluded.
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