[USENIX Security 2026] Attesting Model Lineage by Consisted Knowledge Evolution with Fine-Tuning Trajectory
-
Updated
Sep 14, 2026 - Python
[USENIX Security 2026] Attesting Model Lineage by Consisted Knowledge Evolution with Fine-Tuning Trajectory
LLM distillation detection & model fingerprinting via statistical forensics — behavioral probing, stylistic signatures & representation similarity. CLI + MCP ready.
A protocol for collecting, fusing, and assessing multi-source evidence of model derivation without treating audit signals as automatic legal or royalty verdicts.
AI system governance logger with prompt response and model lineage tracking
Git blame for ML models. Track how your models evolve over time — lineage, data snapshots, performance deltas, and regression debugging for continual learning workflows.
Black-box LLM lineage experiments using lossless compression
To associate your repository with the model-lineage topic, visit your repo's landing page and select "manage topics."