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generative-engine-optimization

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First comprehensive benchmark for Generative Engine Marketing (GEM), an emerging field that focuses on monetizing generative AI by seamlessly integrating advertisements into Large Language Model (LLM) responses. Our work addresses the core problem of ad-injected response (AIR) generation and provides a framework for its evaluation.

  • Updated Nov 18, 2025
  • Python

The official edge-compute middleware for LLM ingestion and GEO (Generative Engine Optimization). Intercepts AI crawlers like SearchGPT, PerplexityBot, and ClaudeBot to deliver structured semantic payloads. Powered by SynSwarm, enterprise SLA by SwarmGeo.

  • Updated Feb 16, 2026
  • Python

To produce a rigorous, primary-source analytical paper that documents the gap between llms.txt’s design intent (inference-time content discovery), the infrastructure reality (WAF/CDN blocking), and actual AI system behavior (no confirmed inference-time usage).

  • Updated Feb 17, 2026
  • TeX

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