SOURCE-LINKED INTELLIGENCE
CHASE: How Content Ecosystems Are Reshaped When Ranking Is the Only Target
Generative Engine Optimization (GEO) is increasingly used to improve content visibility in LLM-based retrieval systems, yet its population-level effects under repeated optimization remain poorly understood. We introduce Content Homogenization under rAnking Signal Exploitation (CHASE), a controlled simulation framework for studying how content ecosystems are reshaped when creators repeatedly adapt documents to an LLM ranking signal. We use ranking as a proxy for source visibility and validate this abstraction against citations in grounded generated responses, obtaining a rank-citation AUC of 0.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T08:53:56.000Z
First collected: 2026-09-21T07:01:58.596Z. This is not the publication date.