mlsanityData to 7 Oct 2026

GPT-Image-2 in the Wild: A Twitter Dataset of Self-Reported AI-Generated Images from the First Week of Deployment

arXiv 2604.25370 ↗First posted 28 Apr 2026cs.CV cs.AIcited by 8

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Abstract (arXiv)

The 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 GPT-image-2 generated images, sourced from publicly available Twitter/X posts in the immediate aftermath of the model's April 21, 2026 release. Leveraging the Twitter API v2 and a multi-stage curation pipeline spanning multilingual text heuristics (English, Japanese, and Chinese), browser-automated Twitter "Made with AI" badge verification, and model name variant matching, we curate 10,217 confirmed GPT-image-2 images from 27,662 collected records over a six-day window. We characterize the dataset across four analyses: CLIP-based zero-shot subject taxonomy, OCR text legibility (82.0% of images contain detectable text), face detection (59.2% of images, 22,583 total faces), and semantic clustering (137 CLIP ViT-L/14 clusters). A key negative result is that C2PA content credentials are systematically stripped by Twitter's CDN on upload, rendering cryptographic provenance verification infeasible for social-media-sourced AI images. The dataset and all curation code are released publicly.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 14 of its 21 references that are in the map. First posted on arXiv 28 Apr 2026.

Builds on

14 of 21 references.

References · 14

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  3. 2019CNN-generated images are surprisingly easy to spot... for nowcited by 842
  4. 2022DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Modelscited by 376
  5. 2023GenImage: A Million-Scale Benchmark for Detecting AI-Generated Imagecited by 318
  6. 2020Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Datacited by 200
  7. 2021Are GAN generated images easy to detect? A critical analysis of the state-of-the-artcited by 139
  8. 2024AMMeBa: A Large-Scale Survey and Dataset of Media-Based Misinformation In-The-Wildcited by 26
  9. 2026How well are open sourced AI-generated image detection models out-of-the-box: A comprehensive benchmark studycited by 15
  10. 2025Can Multi-modal (reasoning) LLMs work as deepfake detectors?cited by 14
  11. 2025Do Deepfake Detectors Work in Reality?cited by 11
  12. 2024Examining the Prevalence and Dynamics of AI-Generated Media in Art Subredditscited by 8
2 more
  1. 2025Synthetic Politics: Prevalence, Spreaders, and Emotional Reception of AI-Generated Political Images on Xcited by 5
  2. 2026GPT4o-Receipt: A Dataset and Human Study for AI-Generated Document Forensicscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 8.

8 papers.

  1. 2026Veritas++: Value-aware On-Policy Distillation for Perception-Enhanced AIGI Detectioncited by 2
  2. 2026ChatGPT Images 2.5 on Forgery Tasks: Testing Advertised Improvements Against Known Answerscited by 2
  3. 2026F-RNG: Feed-Forward Relightable Neural Gaussianscited by 1
  4. 2026Anatomy of a Scam Call: What 10,000 real scam and spam calls reveal about how phone scammers operatecited by 1
  5. 2026Abductive Corroboration of Probabilistic AI Models for Forensic Synthetic Media Detectioncited by 0
  6. 2026Physics-aware Masked Diffusion-based Flood Simulation for Urban Fisheye Disaster Detectioncited by 0
  7. 2026ChatGPT Images 2.5 in the Wild: A Launch-Period Dataset and Detector Evaluationcited by 0
  8. 2026RED: Reconstruction Evolution Dynamics for Generalizable AI-Generated Image Detectioncited by 0