Papers & References

Core Papers

GEO: Generative Engine Optimization

• Authors: Aggarwal, Murahari, Rajpurohit, Kalyan, Narasimhan, Deshpande
• Institutions: Princeton University, IIT Delhi, Adobe Research
• Venue: KDD 2024 (ACM SIGKDD)
• Link: arXiv:2311.09735
• Summary: First academic framework for optimizing content visibility in generative search engines. Tested 9 optimization strategies on 10,000 queries. Key finding: adding statistics improved visibility by +115.1%.
• Detailed summary →

llms.txt Proposal

• Author: Jeremy Howard
• Link: llmstxt.org
• Summary: A proposal for a standardized file that provides information to LLMs about a website. Analogous to robots.txt but designed for AI consumption rather than crawler control.

Industry Reports & Guidelines

Microsoft: Optimizing Content for AI-Powered Search Answers

• Publisher: Microsoft (Bing Webmaster Blog)
• Date: October 2025
• Summary: Official guidelines identifying 3 principles for AI content optimization: Structure, Authority, and Freshness.
• Detailed summary →

Ahrefs: Web Mentions vs Backlinks for AI Visibility

• Publisher: Ahrefs
• Dataset: 75,000 brands
• Summary: Web mentions (brand + keyword) are 3x more predictive of AI visibility than traditional backlinks.

Gartner: The Future of Search

• Publisher: Gartner
• Date: February 2024
• Summary: Prediction that traditional search engine usage will decline by 25% by 2026 as users shift to AI-powered alternatives.

Go Fish Digital: AI Search Conversion Rates

• Publisher: Go Fish Digital
• Summary: Traffic from AI-powered search converts at 25x the rate of traditional search traffic, due to pre-validated user intent.

2025–2026 Updates

The LLMO landscape has moved fast since the original GEO paper. The following sources are tracked as live, primary references.

Cloudflare Radar — AI Insights

• Publisher: Cloudflare
• URL: radar.cloudflare.com/ai-insights
• Type: Live dashboard (continuously updated)
• Relevance: Public data on AI bot crawl share, top AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Bytespider, Google-Extended, etc.), and per-domain AI bot vs. referral ratios. Cloudflare added AI bot blocking in 2024 and has published quarterly trend data through 2025.

OpenAI GPTBot Documentation

• Publisher: OpenAI
• URL: platform.openai.com/docs/bots
• Type: Official crawler disclosure
• Relevance: Canonical reference for GPTBot user agent, IP ranges, robots.txt directives, and opt-out semantics. Updated continuously.

Anthropic Crawler Disclosure

• Publisher: Anthropic
• URL: support.anthropic.com
• Type: Official crawler disclosure
• Relevance: Canonical reference for ClaudeBot, Claude-Web, and Claude-User user agents and how site owners control them.

llms.txt Adoption Tracker

• Publisher: directory.llmstxt.cloud
• URL: directory.llmstxt.cloud
• Type: Community-maintained directory
• Relevance: Tracks sites that have adopted the /llms.txt standard. Adoption widened through 2025 across documentation sites (Anthropic, Mintlify, Stripe-style API docs).

Schema.org Releases (2025)

• Publisher: schema.org
• URL: schema.org/docs/releases.html
• Type: Versioned vocabulary releases
• Relevance: Continued additions to vocabulary used by LLMO Component 2 (Structural Formatting). Track new types relevant to AI consumption (e.g. LearningResource, EducationalOccupationalCredential).

Related Research

Schema.org Structured Data

• URL: schema.org
• Relevance: The vocabulary standard used for JSON-LD structured data implementation in LLMO Component 2 (Structural Formatting).

Google Structured Data Documentation

• URL: developers.google.com/search/docs/appearance/structured-data
• Relevance: Implementation guidelines for structured data that are recognized by both search engines and AI systems.

Contributing

Know a relevant paper or report? Open an issue or submit a pull request to add it to this list.