DeGenTWeb: A First Look at LLM-dominant Websites
Many recent news reports have claimed that content generated by large language models (LLMs) is taking over the web. However, these claims are typically not based on a representative sample of the web and the methodology underlying them is often opaque. Moreover, when aiming to minimize the chances of falsely attributing human-authored content to LLMs, we find that detectors of LLM-generated text perform much worse than advertised. Consequently, we lack an understanding of the true prevalence and characteristics of LLM content on the web. We describe DeGenTWeb which systematically identifies LLM-dominant websites: sites whose content has been generated using LLMs with little human input. ...
| Authors | Sichang Steven He, Calvin Ardi, Ramesh Govindan et al. |
|---|---|
| Primary category | cs.NI |
| Published | 30 April 2026 |
| Last updated at source | 30 April 2026 |
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