CorrDP relaxes standard differential privacy by incorporating feature correlations, enabling distance-dependent noise in DP-ERM for better privacy-utility tradeoffs.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
TabGRAA applies group-relative advantage alignment in an iterative reward-guided post-training loop to improve tabular language model generators on fidelity, utility, and privacy trade-offs across five benchmarks.
MAPLE uses meta-learning with prototypical networks to learn transferable representations and achieves state-of-the-art cross-prompt essay scoring on ELLIPSE, LAILA, and parts of ASAP datasets.
citing papers explorer
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Integrating Feature Correlation in Differential Privacy with Applications in DP-ERM
CorrDP relaxes standard differential privacy by incorporating feature correlations, enabling distance-dependent noise in DP-ERM for better privacy-utility tradeoffs.
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Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training
TabGRAA applies group-relative advantage alignment in an iterative reward-guided post-training loop to improve tabular language model generators on fidelity, utility, and privacy trade-offs across five benchmarks.
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MAPLE: A Meta-learning Framework for Cross-Prompt Essay Scoring
MAPLE uses meta-learning with prototypical networks to learn transferable representations and achieves state-of-the-art cross-prompt essay scoring on ELLIPSE, LAILA, and parts of ASAP datasets.