Author

Zhankai Ye

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#artificial intelligence Preprint Oct 2026

How Narrative Wrapping Affects LLM Refusal: A Cross-Language Benchmark and Defense

Safety-aligned language models often refuse a harmful request stated directly but answer the same request inside a role-play or narrative wrapper. We measure this vulnerability across languages and registers: attack success on Qwen3-1.7B is already 89.4% in English and 93.0% in modern Chinese, and reaches 95.7% in Clas...

Zhan-Kai Ye, Yan-Ning Wang, Yu-Kai Jin et al. · 0 citations

Jul 2026

MUGEN: A Unified Framework for Efficient Motion Understanding and Generation

MUGEN is proposed, a unified motion--language framework that pays neither cost: no codebook, one draw, and surpasses the discrete-token state of the art on every retrieval and alignment metric on SnapMoGen.

Zhankai Ye, Yukai Jin, Bingyang Wei et al. · arXiv.org · 0 citations