AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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BQ-LoRA is proposed, a low-rank adaptation framework that organizes trajectory updates through a local behavior quotient manifold and contains two modules, i.e., behavior quotient balancing (BQB) and decision preserving compression (DPC).
TAC-Merge is proposed for tracing and coordinating cross-layer influence in multimodal model merging and demonstrated the effectiveness in consolidating complementary expert capabilities and supporting generalization to unseen tasks.
This work argues that closing this gap requires alignment at every level of the pipeline, including execution, supervision, optimization, and evaluation, rather than scale alone, and presents Wuying-Browser-Agent, a unified framework that addresses each of these levels.
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