WildAI

License: CC BY-NC-SA 4.0. The WildAI code, models and dataset are released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license: you may use and adapt them for non-commercial purposes, with attribution, and must share adaptations under the same license.

WildAI is a pool of English web documents from Common Crawl (2024 to mid-2026), each labeled by the Pangram AI-text detector as human-written, AI-generated or mixed. It was assembled to build pretraining mixtures with a controlled share of AI-generated text for How Much Is an AI Token Worth? Scaling Laws for Wild AI-Generated Web Text.

WildAI is not a natural sample of the web. An EditLens detector preselected likely-AI documents, so AI text is far more common in the pool than on the web; selection records why each document is in it.

Composition

Config	Source	Documents	GPT-2 tokens
human	common_crawl	4,177,080	2,640,869,930
human	fineweb	54,736,995	37,190,059,660
ai	common_crawl	1,490,771	1,677,945,232
ai	fineweb	31,050,180	32,198,690,948
mixed	common_crawl	262,131	312,479,785
mixed	fineweb	4,325,289	5,268,906,826

Configs

Config	Contents
human, ai, mixed	Pool documents by Pangram label.
labels	Every pool document's metadata and labels, without text.

How it was built

1. Collection. Documents from the Hugging Face FineWeb v1.4.0 dumps CC-MAIN-2024-10 to CC-MAIN-2025-26 (source = fineweb), and from WARC files of the crawls CC-MAIN-2025-30 to CC-MAIN-2026-25 processed with FineWeb's recipe in DataTrove 0.2.0 (source = common_crawl). These crawls were processed from the first 2.6 % of each crawl's WARC files, without FineWeb's MinHash deduplication.
2. Preselection. EditLens (pangram/editlens_Llama-3.2-3B, four buckets, mean over up to three 512-token windows) labeled the collected documents. Documents in its two AI buckets and a crawl-matched draw from its human bucket became candidates (selection = editlens_ai, editlens_human); its lightly-edited bucket was dropped. A label-blind random draw from the 2026 crawls was labeled too (selection = natural).
3. Labeling. Pangram labeled every candidate as Human, Mixed or AI (pangram_label), with the fractions of the text classified AI, AI-assisted and human. Pangram 3.3.2 scored up to three disjoint 512-token windows of each document (the first, middle and last): a document is Human or AI only when every window agrees, and Mixed otherwise, and its fractions are the shares of its windows.
4. Topics and formats. WebOrganizer's topic and format classifiers (WebOrganizer/TopicClassifier, WebOrganizer/FormatClassifier) labeled each document.
5. Pools. Documents were split by Pangram label and deduplicated by id.

Fields

id is the Common Crawl WARC-Record-ID. token_count counts GPT-2 tokens of the released text. truncated marks text shorter than the page's extraction. warc_path is empty for documents taken from Hugging Face FineWeb (its file_path, joined on id, gives it). Sorting a pool by sampling_hash gives its order: any prefix is a uniform sample. pii_anonymized_after_labeling marks rows whose e-mail or IP addresses were replaced at release with FineWeb's placeholders, after the labels were computed on the original text.

Limitations

• Detector labels are not ground truth: Pangram makes errors, and Mixed documents are ambiguous.
• The pool over-represents AI text by design and covers only the crawl files that were processed.
• Deduplication is by document id; the same text can occur under different ids, across crawls.

Personal information and removal requests

Text went through FineWeb's anonymization of e-mail and IP addresses; other personal information may remain. To request removal of content, contact the dataset maintainers through the Hugging Face discussion tab.

License

License: CC BY-NC-SA 4.0. The WildAI code, models and dataset are released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license: you may use and adapt them for non-commercial purposes, with attribution, and must share adaptations under the same license. The full text is in LICENSE. The text comes from FineWeb (ODC-By 1.0) and Common Crawl, and remains subject to Common Crawl's terms of use.

Citation

@article{russell2026wildai,
  title   = {How Much Is an AI Token Worth? Scaling Laws for Wild AI-Generated Web Text},
  author  = {Russell, Jenna and Glickenhaus, Ben and Thai, Katherine and Wieting, John and Iyyer, Mohit and Spero, Max and Emi, Bradley},
  journal = {arXiv preprint arXiv:2609.40295},
  year    = {2026},
  url     = {https://arxiv.org/abs/2609.40295}
}