Research
The research behind GEO: 70+ papers catalogued, the key ones read closely.
How the engines work
Retrieval, ranking and synthesis inside generative engines — what decides which sources reach the answer.
- Read analysis
Retrieval-Augmented Generation for Large Language Models: A Survey
2023 Gao et al. arXiv (v1 2023; v5 2024)
Gao et al. organize RAG into Naive, Advanced, and Modular paradigms, then examine retrieval, generation, augmentation, and evaluation. The survey explains how generative engines use external knowledge, but it does not show which GEO tactics improve visibility.
- Survey
- Open paper
Answer Bubbles: Information Exposure in AI-Mediated Search
2026 Huang et al. Preprint
- Live-engine study
- Open paper
Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
2026 Chu & Hou Preprint
- E-commerce
- Open paper
How LLMs Are Persuaded: A Few Attention Heads, Rerouted
2026 Sun et al. Preprint
- Open paper
Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG
2025 Singh et al. Survey / review
- Agentic search
- Survey
- Open paper
From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents
2025 Zhang et al. Survey / review
- Agentic search
- Survey
- Open paper
A Survey of LLM-based Deep Search Agents: Paradigm, Optimization, Evaluation, and Challenges
2025 Xi et al. Survey / review
- Agentic search
- Survey
- Open paper
Characterizing Web Search in the Age of Generative AI
2025 Kirsten et al. Peer-reviewed
- Live-engine study
GEO methods
What actually moves visibility: content rewrites, structure, and site-side optimization tested against engines.
- Read analysis
What Evidence Do Language Models Find Convincing?
2024 Wan et al. ACL 2024 Main (Long Papers, pp. 7468–7484)
In an ACL 2024 study of conflicting web sources, five LLMs favored topical relevance while giving little weight to scientific references, neutral tone, and formal citations. Every model tested predates mid-2024.
- Benchmark / dataset
- Read analysis
GEO: Generative Engine Optimization
2024 Aggarwal et al. KDD 2024 (Proc. 30th ACM SIGKDD)
Aggarwal et al. coined Generative Engine Optimization and introduced GEO-bench and its impression metrics, reporting visibility gains of up to 40%. The maximum varied by method and domain and was about 22% on Perplexity.ai.
- Benchmark / dataset
- Live-engine study
- Open paper
Diagnosing and Repairing Citation Failures in Generative Engine Optimization
2026 Tian et al. Preprint
- Open paper
Think Before Writing: Feature-Level Multi-Objective Optimization for Generative Citation Visibility
2026 Liu & Xu Peer-reviewed
- Open paper
Generative Engine Optimization: A VLM and Agent Framework for Pinterest Acquisition Growth
2026 Zhang et al. Preprint
- Agentic search
- Multimodal
- Open paper
EcoGEO: Trajectory-Aware Evidence Ecosystems for Web-Enabled LLM Search Agents
2026 Ye et al. Preprint
- Agentic search
- Open paper
IF-GEO: Conflict-Aware Instruction Fusion for Multi-Query Generative Engine Optimization
2026 Zhou et al. Preprint
- Open paper
AgenticGEO: A Self-Evolving Agentic System for Generative Engine Optimization
2026 Yuan et al. Preprint
- Agentic search
- Open paper
Structural Feature Engineering for Generative Engine Optimization: How Content Structure Shapes Citation Behavior
2026 Yu et al. Preprint
- Live-engine study
- Open paper
Optimizing Visibility in Generative Engines: A Critical Survey of Generative Engine Optimization (2023–2026)
2026 Martinez Survey / review
- Survey
- Open paper
Designing Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability
2026 Elnaffar & Rashidi Preprint
- Agentic search
- E-commerce
- Open paper
Beyond Retrieval: Modeling Confidence Decay and Deterministic Agentic Platforms in Generative Engine Optimization
2026 Zhao et al. Preprint
- Agentic search
- Open paper
Mind Reader: Latent User Demand-Guided Content Optimization for Generative Search Engine
2026 Chen et al. Peer-reviewed
- Open paper
What Generative Search Engines Like and How to Optimize Web Content Cooperatively
2025 Wu et al. Preprint
- Open paper
White Hat Search Engine Optimization using Large Language Models
2025 Bardas et al. Preprint
- Open paper
Role-Augmented Intent-Driven Generative Search Engine Optimization
2025 Chen et al. Preprint
- Open paper
Generative Engine Optimization: How to Dominate AI Search
2025 Chen et al. Preprint
- Live-engine study
- Open paper
Beyond SEO: A Transformer-Based Approach for Reinventing Web Content Optimisation
2025 Lüttgenau et al. Preprint
- Open paper
Rewrite-to-Rank: Optimizing Ad Visibility via Retrieval-Aware Text Rewriting
2025 Ho et al. Preprint
- E-commerce
- Open paper
LLMs.txt Adoption and Impact on AI Visibility: A 300K-Domain Study
2025 SE Ranking Industry study
Measurement & evaluation
Visibility metrics, citation behaviour, benchmarks, and how many samples a reliable reading takes.
- Read analysis
C-SEO Bench: Does Conversational SEO Work?
2025 Puerto et al. NeurIPS 2025 Datasets and Benchmarks Track (Advances in Neural Information Processing Systems 38)
C-SEO Bench found that most of the ten white-hat conversational SEO rewrites did not reliably improve citation rank and often made it worse. Retrieval order had a stronger effect, while gains declined as competitors adopted the same method.
- Benchmark / dataset
- Open paper
Navigating the Shift: A Comparative Analysis of Web Search and Generative AI Response Generation
2026 Chen et al. Preprint
- Open paper
Disentangling Answer Engine Optimization from Platform Growth: A Log-Based Natural Experiment on ChatGPT Referral Traffic
2026 Watanabe & Nakayashiki Preprint
- Live-engine study
- Publisher economics
- Open paper
From Citation Selection to Citation Absorption: A Measurement Framework for GEO Across AI Search Platforms
2026 Zhang et al. Preprint
- Benchmark / dataset
- Live-engine study
- Open paper
SAGEO Arena: A Realistic Environment for Evaluating Search-Augmented Generative Engine Optimization
2026 Kim et al. Preprint
- Benchmark / dataset
- Open paper
Generative Engine Optimization at Scale: Measuring Brand Visibility Across AI Search Engines
2026 Kumar Preprint
- Live-engine study
- Open paper
Whose Hotel Does the AI Recommend? An Algorithm Audit of Reputation Signals in LLM-Assisted Hotel Selection
2026 Baig et al. Preprint
- E-commerce
- Open paper
Algorithmic Trust and Compliance: Benchmarking Brand Notability for UK iGaming Entities in Generative Search Engines
2026 Oruesagasti Industry study
- Live-engine study
- Open paper
Evaluating Reliability Asymmetries in Chinese Factual Search and AI Answers
2026 Liu et al. Preprint
- Chinese engines
- Benchmark / dataset
- Live-engine study
- Open paper
The Rise of AI Search: Implications for Information Markets and Human Judgement at Scale
2026 Aral et al. Preprint
- Live-engine study
- Open paper
Cultural Encoding in Large Language Models: The Existence Gap in AI-Mediated Brand Discovery
2026 Huang et al. Preprint
- Chinese engines
- Benchmark / dataset
- Open paper
The End of Rented Discovery: How AI Search Redistributes Power Between Hotels and Intermediaries
2026 Zhu & Chang Preprint
- E-commerce
- Live-engine study
- Publisher economics
- Open paper
E-GEO: A Testbed for Generative Engine Optimization in E-Commerce
2025 Bagga et al. Preprint
- E-commerce
- Benchmark / dataset
- Open paper
Source Coverage and Citation Bias in LLM-based vs. Traditional Search Engines
2025 Zhang et al. Preprint
- Open paper
CC-GSEO-Bench: A Content-Centric Benchmark for Measuring Source Influence in Generative Search Engines
2025 Chen et al. Preprint
- Benchmark / dataset
- Open paper
Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy
2025 Hu et al. Peer-reviewed
- Live-engine study
- Open paper
AI Answer Engine Citation Behavior: An Empirical Analysis of the GEO-16 Framework
2025 Kumar & Palkhouski Preprint
- Live-engine study
- Open paper
Assessing Web Search Credibility and Response Groundedness in Chat Assistants
2025 Vykopal et al. Peer-reviewed
- Live-engine study
- Open paper
News Source Citing Patterns in AI Search Systems
2025 Yang Preprint
- Live-engine study
- Publisher economics
- Open paper
Search Engines in an AI Era: The False Promise of Factual and Verifiable Source-Cited Responses
2024 Venkit et al. Preprint
- Open paper
Generative AI Search Engines as Arbiters of Public Knowledge: An Audit of Bias and Authority
2024 Li & Sinnamon Peer-reviewed
- Live-engine study
Manipulation & defense
Ranking attacks, prompt injection and content poisoning — and the defenses proposed against them.
- Open paper
Multimodal Generative Engine Optimization: Rank Manipulation for Vision-Language Model Rankers
2026 Du et al. Preprint
- Multimodal
- Open paper
GEO-Bench: Benchmarking Ranking Manipulation in Generative Engine Optimization
2026 Nimase et al. Preprint
- Benchmark / dataset
- Open paper
Controlling Output Rankings in Generative Engines for LLM-based Search
2026 Jin et al. Preprint
- E-commerce
- Open paper
Exploring LLM Biases to Manipulate AI Search Overview
2026 Smirnov Preprint
- Open paper
GPE: Evaluating Robust Evidence Aggregation for Fact Verification under Controllable GEO-Style Poisoning
2026 Wang et al. Preprint
- Benchmark / dataset
- Open paper
SafeGEO: Understanding Generative Engine Optimization Risks in Recommendation Agents
2026 Wen et al. Preprint
- E-commerce
- Benchmark / dataset
- Open paper
SCI-Defense: Defending Manipulation Attacks from Generative Engine Optimization
2026 Yu et al. Preprint
- E-commerce
- Open paper
Ranked by Position: Order Sensitivity as an Exploitable Attack Surface in LLM Listwise Recommenders
2026 Zhang et al. Preprint
- E-commerce
- Open paper
SIREN: PAIR-Driven Preference Manipulation in Web-RAG Recommenders
2026 Caville et al. Preprint
- Open paper
StealthRank: LLM Ranking Manipulation via Stealthy Prompt Optimization
2025 Tang et al. Preprint
- Open paper
GASLITEing the Retrieval: Exploring Vulnerabilities in Dense Embedding-based Search
2025 Ben-Tov & Sharif Peer-reviewed
- Open paper
PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation
2025 Chen et al. Peer-reviewed
- Benchmark / dataset
- Open paper
GRADA: Graph-based Reranking against Adversarial Documents Attack
2025 Zheng et al. Peer-reviewed
- Open paper
ReliabilityRAG: Effective and Provably Robust Defense for RAG-based Web-Search
2025 Shen et al. Peer-reviewed
- Open paper
The Ranking Blind Spot: Decision Hijacking in LLM-based Text Ranking
2025 Qian et al. Peer-reviewed
- Open paper
Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization
2025 Xing et al. Peer-reviewed
- Open paper
Ranking Manipulation for Conversational Search Engines
2024 Pfrommer et al. Peer-reviewed
- Open paper
Manipulating Large Language Models to Increase Product Visibility
2024 Kumar & Lakkaraju Preprint
- E-commerce
Policy & governance
Publisher economics, attribution, copyright, and the regulation forming around AI answers.
- Open paper
The Impact of AI Search on the Online Content Ecosystem: Evidence from Google and Reddit
2026 Zhang et al. Preprint
- Live-engine study
- Publisher economics
- Open paper
An Economic Framework for Generative Engines: Advertising or Subscription?
2026 Zhang et al. Preprint
- Publisher economics
- Open paper
Impact of AI Search Summaries on Website Traffic: Evidence from Google AI Overviews and Wikipedia
2026 Khosravi & Yoganarasimhan Preprint
- Live-engine study
- Publisher economics
- Open paper
Do AI Overviews Benefit Search Engines? An Ecosystem Perspective
2026 Wu et al. Preprint
- Publisher economics
- Open paper
Google users are less likely to click when an AI summary appears
2025 Pew Research Center Industry study
- Live-engine study
- Publisher economics