Researchllmranking manipulationshadow modelsreasoning augmentation
Researchers Demonstrate CORE Manipulates LLM-Based Search Rankings
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Researchers published a study demonstrating CORE, an optimization method that systematically influences LLM-based search rankings, testing Claude-4, Gemini-2.5, GPT-4o and Grok-3 via API. Query-based CORE achieved roughly 77–82% Top-1 promotion while shadow-model approaches (with Llama-3.1-8B proxy) showed lower but transferable gains, and reasoning- versus review-based augmentations affected models differently.
