AI Research
Grokers: Bottom-Up Inductive Comprehension and Write-Time Intelligence over Typed Knowledge Graphs
A new architecture for persistent knowledge graph comprehension that eliminates redundant LLM inference costs.
We present Grokers, an architecture for building persistent, structured comprehension of typed knowledge graphs through bottom-up inductive traversal of dependency subgraphs. Unlike retrieval-augmented generation (RAG), which pays full comprehension cost at every query, Grokers p...
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ArXiv CS.AI
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ArXiv CS.AI
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Grokers shifts the computational burden of AI comprehension from query time to write time, enabling persistent, structured knowledge. By utilizing dependency subgraphs and formal theorems, it achieves near-perfect cache hits and reduces reliance on expensive language model calls.
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