AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces an inclined boundary that evaluates prediction loss relative to predictive entropy, and shows that entropy correction can preserve the expected membership signal while reducing its variance, thereby improving standardized member--non-member separation.
LT-MKT first integrates textual information from questions and their associated concepts to construct a Multi-domain Hierarchical Graph, leveraging the advanced representational capabilities of large language models (LLMs) to bridge isolated domains and proposes a novel method incorporating cognitive Load and knowledge...
AD-Reranker is proposed, a novel framework that shifts reranker training from proxy imitation to answer-driven utility optimization, and reformulate the reranker as an environment-grounded agent that interacts with a downstream reader, modeled as a deterministic environment.
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