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• CrossAdapt is a two-stage framework for efficient cross-architecture knowledge transfer.method 95%
• The offline stage of CrossAdapt enables rapid embedding transfer via dimension-adaptive projections without iterative training.method 95%
• CrossAdapt achieves 0.27-0.43% AUC improvements on three public datasets.result 95%
• CrossAdapt reduces training time by 43-71% on three public datasets.result 95%
• The online stage of CrossAdapt introduces asymmetric co-distillation.method 95%
• Large-scale deployment on Tencent WeChat Channels demonstrates CrossAdapt's effectiveness in mitigating AUC degradation.result 95%
• Existing knowledge distillation methods struggle with architectural heterogeneity.limitation 90%

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