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Benchmarking Neural Defend ARCAS 1B: A Foundational Multimodal Deepfake Detection Model
AI-generated imagery evolves faster than benchmark-specific detector evaluations, making a single score an incomplete account of generalization. This paper evaluates Neural Defend ARCAS 1B across benchmark families without benchmark-specific parameter updates. We retain native aggregation and supplement it with record-level measures, coverage accounting, and subgroup diagnostics. Each Results subsection identifies the release and evaluation population, reports the official metric, and describes observed error patterns. A combined analysis synthesizes shared patterns while preserving the distin
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- arXiv · AI, language, vision and robotics · 2026-09-21T09:15:02.000Z
First collected: 2026-09-23T08:01:43.213Z. This is not the publication date.