AI Citation Optimization

Research from OpenAI on [Citations in ChatGPT](https://help.openai.com) and Google's documentation on [Generative AI Overviews](https://developers.google.com/search/docs/fundamentals/how-search-works#generative-ai) confirms that source attribution is driven by factual accuracy and site authority.

From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms — Researchers analyzing 21,143 citations found that citation influence and citation frequency are different, showing that optimization should focus on absorption rather than citation counts alone. https://arxiv.org/abs/2604.25707

What Gets Cited: Competitive GEO in AI Answer Engines — Across 252,000 experiments, researchers found that topical relevance, list position, recent timestamps, and explicit facts significantly increase the probability of being cited first. https://arxiv.org/abs/2605.25517

Diagnosing and Repairing Citation Failures in Generative Engine Optimization — AgentGEO improved citation rates by more than 40% while modifying only 5% of content, demonstrating that targeted citation optimization outperforms generic rewriting. https://arxiv.org/abs/2603.09296

GEO: Generative Engine Optimization — Researchers showed that adding citations, quotations, and statistics can improve visibility in AI-generated answers by up to 40%, establishing one of the first foundations for citation optimization. https://arxiv.org/abs/2311.09735