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.
High novelty, broad scope, and direct exploitability; limited by API-only tests and lack of consumer-interface evaluation.
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