RPSG generates realistic synthetic replicas of private text by combining private seeds with public LLMs and a formal differential privacy mechanism in candidate selection.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
KD outperforms SFT for LLM post-training in low-data regimes but the advantage fades with abundant data unless the teacher is stronger; a two-stage strategy aids domain-specific low-resource cases.
citing papers explorer
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Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation
RPSG generates realistic synthetic replicas of private text by combining private seeds with public LLMs and a formal differential privacy mechanism in candidate selection.
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Understanding Knowledge Distillation in Post-Training: When It Helps and When It Fails
KD outperforms SFT for LLM post-training in low-data regimes but the advantage fades with abundant data unless the teacher is stronger; a two-stage strategy aids domain-specific low-resource cases.