arXiv:2610.26946v1 Announce Type: new Abstract: Large language models can assist forensic report drafting, but fluent output does not ensure evidentiary reliability. This study presents an evidence-grounded framework for evaluating LLM-assisted Android forensic reports at the atomic-claim level. Gemini, Llama, and Qwen each generated reports for two controlled cases: a public Android 13 dataset and a physical LG device with a zero-reportable-fact boundary.
Evidence-Grounded LLM-Assisted Android Mobile Forensic Reporting
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