AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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ESRL is introduced, an architecture-aware framework that explicitly explores the expert-routing space of MoE models, and preserves high-confidence experts as anchors, and restricts stochastic routing to a plausible candidate pool, thereby retaining reliable computation paths.
Experimental results on CAIL2018 demonstrate that legal-oriented adaptation based on DRAGIN improves retrieval-augmented reasoning in this Chinese legal judgment prediction setting while maintaining low retrieval overhead.
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