Contrastive Decoding Diffing (CDD): recovering verbatim finetuning data from logits alone, no weight access needed[R]

Summary

We built a model diffing method that recovers verbatim content from narrowly finetuned LLMs using only grey-box logit access (no weights, no activations, no probe corpus). Recent work (Minder, Dumas et al., "Narrow Finetuning Leaves Clearly Readable Traces in Activation Differences") showed that finetuning leaves detectable traces in activation differences between base and finetuned models. Their method, Activation Difference Lens (ADL), steers generation using these differences, but i

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