Author

Di Hong

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#artificial intelligence Preprint Sep 2026

CollageAttack: Exploiting Cross-Modal Alignment Flaws in T2I Models through Spatial Text Composition

Text-to-image (T2I) models have substantially improved in language understanding, in-image text rendering, and visual composition, while their safety mechanisms do not always keep pace with these capabilities. This creates a cross-modal attack surface in which harmful semantics can remain inconspicuous in a serialized...

Zhi-Yi Mou, Yao Lu, Wang-Ze Ni et al. · 0 citations

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.

Ze-Feng Wu, Weiwei Qi, Jielong Chen et al. · 4 citations