arXiv Artificial Intelligence

SafeGEO: Understanding Generative Engine Optimization Risks in Recommendation Agents

5 hours ago 10.09.2026 07:00 👁 1 views
SafeGEO: Understanding Generative Engine Optimization Risks in Recommendation Agents

Quick summary

arXiv:2606.28356v2 Announce Type: replace-cross Abstract: Generative Engine Optimization (GEO) lets content owners rewrite web content to increase their visibility in generative systems. In recommendation agents, this creates a risk that sources controlled by sellers make flawed products appear better supported than they are. We study this risk at the generation stage by asking whether recommendation agents continue to make decisions that align with user utility when these sources are rewritten for GEO. To make this question measurable, we construct SafeGEO, an evaluation suite with 22 GEO att

Key takeaways

  • arXiv:2606.28356v2 Announce Type: replace-cross Abstract: Generative Engine Optimization (GEO) lets content owners rewrite web content to increase their visibility in generative systems.
  • In recommendation agents, this creates a risk that sources controlled by sellers make flawed products appear better supported than they are.
  • We study this risk at the generation stage by asking whether recommendation agents continue to make decisions that align with user utility when these sources are rewritten for GEO.

Why it matters

“SafeGEO: Understanding Generative Engine Optimization Risks in Recommendation Agents” highlights the need for repeatable measurement rather than a single impressive demonstration. Independent validation across datasets and clearly stated limitations determine whether a result can guide product decisions.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗