Training Leaves Traces: Centered Residual Signatures for Language Model Lineage Verification
Open-weight language models are fine-tuned, quantized, pruned, and merged, yet their provenance is often undocumented. We study data-free white-box lineage verification: can weights alone reveal whether two compatible model checkpoints share ancestry? Residual training produces a shared identity-aligned component in branch products, so this structure alone cannot establish ancestry. We remove it and compare checkpoint-specific structure across residual blocks, yielding a symmetric lineage score calibrated against independent checkpoints. On residual-MLP and GPT-2 benchmarks, the score separates fine-tuned, LoRA-merged, pruned, and quantized descendants from independent and distilled model...
| Authors | Aman Singh Thakur, Rayan Khoury |
|---|---|
| Primary category | cs.CL |
| Published | 14 August 2026 |
| Last updated at source | 22 September 2026 |
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