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Agentic GraphRAG is the fastest-moving corner of graph research in 2026. This article breaks down the pattern taxonomy — tool-calling, RL-trained…
Graph foundation models are 2026's most visible graph-ML story: one pretrained model reasoning over any graph, and what it promises production.
A practical comparison of GraphQL and SPARQL as query layers over knowledge graphs — data model differences, transitive closure gaps, federation…
Multimodal knowledge graphs add images, audio, 3D and spatiotemporal structure: construction, MLLM-guided completion, multimodal GraphRAG, and benchmarks.
Graph query languages are the fastest-growing — and thinnest — research cell: the 2026 GQL wave, NL2GQL, expressive power, query layer as product surface.
Open-source intelligence has always been a graph problem: entities, relationships, provenance. The 2026 shift is that generative and agentic AI can do the investigation part too. This article reviews the emerging OSINT+graph research: entity resolution, temporal threat intelligence, agentic collection, and the hallucination risk that makes graphs essential.