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Ping Chen

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Preprint Aug 2026

Measuring the Wrong Thing: Internal Harmfulness Scores Anti-Rank Successful Jailbreaks

Internal safety scores judge a prompt before any text is generated, and they are validated by how well they separate harmful prompts from benign ones, so Active Attention Probing is introduced, which supplies a fixed content independent measurement coordinate.

Ming-Yu Luo, Ming Deng, Zilang Qiu et al. · 0 citations
Open access Sep 2026

MimicDB: Runtime Defense against Wrong-Result Bugs in Database Query Optimizers via Query-Rewriting Diversity

These findings characterize the potential of single-engine diversity to detect wrong-result failures and select correct results, together with the execution costs and reference-validity constraints that shape its practical use.

Ze-Lin Wang, Ping Chen, Jin Wei et al. · 0 citations
#small language model Review Sep 2026

Detecting and Localizing Segment-Level Poisoning in Multi-Source LLM-Agent Inputs

ActProbe, an internal-state-based framework for detecting and localizing poisoned segments in multi-source LLM inputs, is proposed and remains effective against defense-aware adaptive attacks and can protect black-box APIs through surrogate-based poisoned-segment removal.

Xue Tan, Chang-Hui Wang, Sanrui Yang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

A Trustworthy Watermarking Framework for LLM-Generated Food Safety Content

ToSS (Token Oriented Repartitioning and Strategic Selection), a reliable authentication method using adaptive dual watermarking that divides vocabulary tokens into black and white sublists, enabling precise bit-level embedding of traceability information.

Zhongli Fang, Yi-Ran Chen, Ling-Yun Zhang et al. · 0 citations
Jul 2026

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems

AcMAS is proposed, an activation-based framework for malicious-behavior detection in MAS that significantly outperforms graph-based baselines against stealthy attacks, with generalization across diverse open-source LLM backbones, attack intensity, and MAS scale.

Haowen Xu, Xue Tan, Lei Ma et al. · 0 citations

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