AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This survey focuses on four fundamental data-centric challenges: (1) Incompleteness, real-world graphs have missing nodes, edges, (2) Missing nodes, edges, and (3) Missing edges.
This work constructs multiple entity co-occurrence networks using two tools (Fast Entity Linker and DBpedia Spotlight) and numerous confidence thresholds for each and proves that standard network analysis metrics, such as size, connectivity, and centrality are all heavily influenced by the choice of entity linking tool.
A systematic comparison of retrieval strategies for candidate generation under a shared LLM-based selection stage, combining sparse retrieval (BM25), Web KB search, and a state-of-the-art trained dense retriever with several open- and closed-source LLMs is presented.
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