Author

Weiwei Qi

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Preprint Jul 2026

DataShield: Uncovering Risky Fine-Tuning Data Across LLMs Through Consensus Subspace Alignment

DataShield is a data assessment framework that identifies risky fine-tuning samples and response segments through consensus subspace alignment over joint safety-critical semantic spaces derived from multiple safety-aligned LLMs, allowing both sample-level filtering and fine-grained segment-level masking.

Zefeng Wu, Weiwei Qi, Jielong Chen et al. · 4 citations