Don't Guess, Escalate: Towards Explainable Uncertainty-Calibrated AI Forensic Agents
Fuente:
arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866915684704845824 |
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| author | Boato, Giulia Montibeller, Andrea Delp, Edward Verdoliva, Luisa Miorandi, Daniele |
| author_facet | Boato, Giulia Montibeller, Andrea Delp, Edward Verdoliva, Luisa Miorandi, Daniele |
| contents | AI is reshaping the landscape of multimedia forensics. We propose AI forensic agents: reliable orchestrators that select and combine forensic detectors, identify provenance and context, and provide uncertainty-aware assessments. We highlight pitfalls in current solutions and introduce a unified framework to improve the authenticity verification process. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_16614 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Don't Guess, Escalate: Towards Explainable Uncertainty-Calibrated AI Forensic Agents Boato, Giulia Montibeller, Andrea Delp, Edward Verdoliva, Luisa Miorandi, Daniele Multiagent Systems Artificial Intelligence Computer Vision and Pattern Recognition Multimedia AI is reshaping the landscape of multimedia forensics. We propose AI forensic agents: reliable orchestrators that select and combine forensic detectors, identify provenance and context, and provide uncertainty-aware assessments. We highlight pitfalls in current solutions and introduce a unified framework to improve the authenticity verification process. |
| title | Don't Guess, Escalate: Towards Explainable Uncertainty-Calibrated AI Forensic Agents |
| topic | Multiagent Systems Artificial Intelligence Computer Vision and Pattern Recognition Multimedia |
| url | https://arxiv.org/abs/2512.16614 |