Counter-GEO-Bench: Evaluating Defenses Against Information-Distorting Generative Engine Optimization

Abstract

Generative engine optimization (GEO) enables content producers to increase the visibility of their web pages in generative search engines, but the same techniques can deliver targeted misinformation when adversaries publish ordinary-looking GEO-optimized documents that victim large language models (LLMs) retrieve and synthesize into distorted answers. No existing benchmark evaluates defenses against this threat under controlled conditions. Therefore, we present Counter-GEO-Bench, a defense bench

Categories

@misc{zheng2026countergeobench,
  title = {{Counter-GEO-Bench: Evaluating Defenses Against Information-Distorting Generative Engine Optimization}},
  author = {Bing Zheng and Zongyao Zhao and Wenming Yang},
  year = {2026},
  month = sep,
  eprint = {2609.02316},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.02316}
}