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. We evaluate these claims on four forgery tasks with answers fixed in advance: receipt-field alteration, repeated editing, product placement...
Ankit Raj, Yu-Xin Zhang, Kidus Zewde et al.· 2 citations
AI agents that carry a multi-step computer task through on their own became ordinary tools in the past year, and the same autonomy is available to anyone whose task is harmful. We ask what that means for a relying party -- an insurer, a lender, an auditor -- whose evidence is a filed PDF. AgentForge-Bench measures how...
Si-Miao Ren, Ankit Raj, Tommy Duong et al.· 0 citations
Screening a phone call for fraud needs a trustworthy probability after every caller turn, in milliseconds. Jev-style typed decisions promise exactly that: declared options go in, one calibrated probability per option comes out of a single forward pass, with no generated text. We test an open implementation of this read...
The frozen collection of ChatGPT Images 2.5 supports analysis of reported model use during a product transition, with source and attribution evidence retained for interpretation, and is released at https://scam.ai/research.
This work presents CallScreenBench, which reports five automated call-and-note measure groups motivated by owner endorsement, and reports quality measures and guardedness channels separately so that a single pass/fail score does not hide their trade-offs.
Jia-Qi Gan, Hao Tang, Jamey Z. Liang et al.· 1 citation
This work analyzes a complete corpus of 10,211 inbound scam and spam calls collected over 54 days by an AI voice-agent honeypot that answered callers and kept them talking, and introduced in a companion data descriptor.
Ethan Traister, Ankit Raj, Jiaqi Gan et al.· 0 citations
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