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A training-free agentic framework built around specialist detectors, per-detector triage, and conflict-aware evidence arbitration is studied, indicating that the main challenge of open-world image forensics is not detecting manipulations, but calibrating trust in specialized forensic tools and arbitrating conflicting evidence.
Collusion attacks can render traditional model fingerprinting ineffective, but this new method not only embeds fingerprints but also sabotages the quality of colluded outputs.