Data Cartography for Detecting Memorization Hotspots and Guiding Data Interventions in Generative Models

• URL: http://arxiv.org/abs/2509.00083v1
• Date: Wed, 27 Aug 2025 05:11:06 GMT
• Title: Data Cartography for Detecting Memorization Hotspots and Guiding Data Interventions in Generative Models
• Authors: Laksh Patel, Neel Shanbhag,
• Abstract summary: Modern generative models risk overfitting and unintentionally memorizing rare training examples, which can be extracted by adversaries or inflate benchmark performance.<n>We propose Generative Data Cartography (GenDataCarto), a data-centric framework that assigns each pretraining sample a difficulty score (early-epoch loss) and a memorization score (frequency of forget events'')<n>We prove that our memorization score lower-bounds classical influence under smoothness assumptions and that down-weighting high-memorization hotspots provably decreases the generalization gap via uniform stability bounds.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Modern generative models risk overfitting and unintentionally memorizing rare training examples, which can be extracted by adversaries or inflate benchmark performance. We propose Generative Data Cartography (GenDataCarto), a data-centric framework that assigns each pretraining sample a difficulty score (early-epoch loss) and a memorization score (frequency of ``forget events''), then partitions examples into four quadrants to guide targeted pruning and up-/down-weighting. We prove that our memorization score lower-bounds classical influence under smoothness assumptions and that down-weighting high-memorization hotspots provably decreases the generalization gap via uniform stability bounds. Empirically, GenDataCarto reduces synthetic canary extraction success by over 40\% at just 10\% data pruning, while increasing validation perplexity by less than 0.5\%. These results demonstrate that principled data interventions can dramatically mitigate leakage with minimal cost to generative performance.

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