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cs.CV2026

ChatGPT Images 2.5 in the Wild: A Launch-Period Dataset and Detector Evaluation

Dennis Ng, Xingyu Shen, Ankit Raj +6

An image tool can change its underlying generator while retaining its public name, making version attribution from online posts ambiguous. We study this problem after the ChatGPT I…

cs.CV2026

ChatGPT Images 2.5 on Forgery Tasks: Testing Advertised Improvements Against Known Answers

Ankit Raj, Yuxin Zhang, Kidus Zewde +7

OpenAI released ChatGPT Images 2.5 on 8 September 2026, advertising more precise local edits, better consistency across edits, more faithful reference products and sharper detail.…

cs.CV2026

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

Kidus Zewde, Simiao Ren, Xingyu Shen +6

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…

cs.CV2026

When the Forger Is the Judge: GPT-Image-2 Cannot Recognize Its Own Faked Documents

Jiaqi Wu, Yuchen Zhou, Dennis Tsang Ng +5

OpenAI's GPT-Image-2 has effectively erased the visual boundary between authentic and AI-edited document images: a single number on a receipt can be replaced in under a second for…

cs.CV2026

A Synthetic Eye Movement Dataset for Script Reading Detection: Real Trajectory Replay on a 3D Simulator

Kidus Zewde, Yuchen Zhou, Dennis Ng +6

Large vision-language models have achieved remarkable capabilities by training on massive internet-scale data, yet a fundamental asymmetry persists: while LLMs can leverage self-su…

cs.CV2026

Can a Teenager Fool an AI? Evaluating Low-Cost Cosmetic Attacks on Age Estimation Systems

Xingyu Shen, Tommy Duong, Xiaodong An +6

Age estimation systems are increasingly deployed as gatekeepers for age-restricted online content, yet their robustness to cosmetic modifications has not been systematically evalua…