wu-beining/geo-research-hub

GEO Research Hub is a curated research repository tracking the academic and engineering progress in Generative Engine Optimization (GEO), the practice of making web content more likely to be cited or referenced by AI-powered search engines and chat assistants, rather than just ranking well in traditional web search. Related terms covered include Answer Engine Optimization (AEO), Conversational SEO, and Generative Search Optimization. The project aims to be more than a simple list of links. Its stated goal is to organize papers, benchmarks, open-source implementations, platform policies, and industry signals from 2024 onward into a knowledge base that can answer three questions: what genuine academic and engineering progress has been made in GEO, which work is merely repackaging existing ideas, and what research and experiments should come next. The repository organizes its contents into tables covering academic papers, publicly available benchmark datasets, and open-source GitHub projects. Papers tracked include foundational GEO work from KDD 2024, evaluation benchmarks from NeurIPS 2025, optimization learning systems from ICLR 2026, and multi-agent GEO approaches from ACL Findings 2026. Each paper entry links back to its source paper and, where one exists, an associated code repository or dataset hosted on GitHub or Hugging Face. The safety-related angle, covering adversarial manipulation of AI search rankings, is also tracked as a separate category. The README itself is written in Chinese, and the repository is written in TeX, suggesting it may also be compiled into a document. The maintainer frames the current state of the field as having moved past simply rewriting content to be cited more, toward optimizing across retrieval, ranking, generation, attribution, and defense against manipulation all at once. The full README is longer than what was provided.