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Unauthorized model distillation, in which a model is trained on the outputs of a proprietary large language model (LLM), is a growing threat to model providers. We study distillation inference: determining whether a suspect model was distilled from another model or trained independently. We formulate this problem as a...
This paper systematically analyzes the privacy risks associated with dot maps and presents AutoLocate, an automated framework for high-precision location recovery that achieves average recovery errors as low as 1 meter on small-scale maps of the United States, over 200x more accurate than existing approaches.
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