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A compact extractor can outperform larger models in knowledge-graph construction, achieving up to 84% evidence recall in GraphRAG tasks.
A judge-orchestrated ensemble of diverse LLMs trounces single models in multi-turn response generation, proving that strategic model selection beats brute force scaling.