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Zi-Han Dong

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#artificial intelligence Preprint Sep 2026

Style Over Substance: Content-Invariant Wrappers Flip LLM Safety-Judge Verdicts

Automatic safety judges -- for example Llama Guard, or GPT-4o given a grading prompt -- produce the numbers behind reported jailbreak success rates, defense evaluations, and safety leaderboards. We ask whether these judges grade what a reply contains or how it sounds. We place a fixed piece of text before or after a mo...

Yong-Xin Zhou, Wen-Bo Ye, Yuan-Zhe Liu et al. · 0 citations
Jul 2026

How Benchmarks Mis-Score Computer-Use Agents

A three-tier diagnostic taxonomy shows that verification/feedback and planning failures dominate execution/grounding errors, while a single scalar success rate can not explain, and connects these findings to newer long-horizon CUA benchmarks and derive stage-specific design rules for CUA evaluation.

Zi-Han Dong, Zhiyuan Ma, Zekun Wang et al. · 2 citations
#artificial intelligence Preprint Aug 2026

Single Canonical Prompts Underestimate LLM Safety's Surface-Form Sensitivity

A benchmark score is a measurement instrument, yet most benchmarks read each item at a single canonical surface form. We ask whether that reading is faithful: when an item's intent is held fixed and only its meaning-preserving surface form varies, does the canonical-form score estimate model behavior well, and how much...

Yongxin Zhou, Jun-Wei Yao, Yuanzhe Liu et al. · 1 citation
Preprint Aug 2026

Hybrid-Policy Self-Editing for Composable Unstructured Knowledge Editing

HPSE is proposed, which builds a hybrid rollout that steps in to place missing facts onto the student's own trajectory precisely where its coverage fails, while staying on-policy elsewhere.

Tian-Ci Liu, Zi-Han Dong, Tian-Chun Li et al. · 0 citations

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