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Shouling Ji

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Preprint Sep 2026

The Shape of Ownership: Verifying LLM Provenance through Semantic Structures

This work introduces PROSE (Provenance through Relational Organization of Semantic Expression), replacing fixed query sets with a target semantical domain and brittle response keys with semantic structures internalized as domain-conditioned response behavior.

Zhong-Rui Sun, Jia-Hao Chen, Ou-Bo Ma et al. · 0 citations
#artificial intelligence Review May 2026

IntraGuard: Committee-Side Defenses Against Review Outsourcing to Commercial Chatbots

IntraGuard is proposed, a black-box, venue-agnostic defense framework grounded in the structural--visual decoupling inherent to the PDF that achieves a defense success rate of up to 84%, while preserving peer-review invariance for human reviewers.

Ou-Bo Ma, Rui-Xiao Lin, Jia-Hao Chen et al. · 2 citations
Jul 2026

Decision-Level Hijacking: Injecting Cognitive Bias into Large Language Models via Bit-Flip Attacks

It is revealed that Bit-Flip Attacks (BFAs) can serve as an attack vector for inducing decision-level hijacking, requiring no real-time interaction or control over the training process, and only a minimal number of weight bits need to be flipped after deployment to achieve stealthy, low-cost, and persistent cognitive m...

Yu Yan, Jia-Hao Chen, Si-Qi Lu et al. · 0 citations
Preprint Sep 2026

A Finger on the Scale: Covert Policy Steering through Agentic Skills

SkillShift is presented, a constrained black-box framework for covert policy steering without explicit target command injection or task hijacking that combines semantically plausible policy edits with hierarchical validation, failure-guided optimization, and strategy compression to preserve effectiveness, output validi...

Jia-Rui Li, Jia-Hao Chen, Chun-Yi Zhou et al. · 0 citations
Jul 2026

Lilith: Backdoor Generalization under Training-Inference Trigger Shift

This work forms this problem as backdoor generalization under training--inference trigger shift and introduces Lilith, a black-box anchor-to-family framework that achieves high family-wise attack success with limited utility degradation and a small trigger generalization gap.

Zhou Feng, Jia-Hao Chen, Chun-Yi Zhou et al. · 0 citations

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