Author

Hai-Zhong Zheng

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Preprint Sep 2026

Self-Evolving Defense: Continual Security Policy Learning for LLM Agents

Large language models (LLMs) increasingly power agents that access sensitive information, use external tools, and modify software repositories. Although these capabilities offer substantial benefits, they also create security risks such as jailbreaks, prompt injection, and vulnerable code generation. Existing defenses...

Minh Nhat Le, Nisarga Gondi, Yi-Bo Peng et al. · 0 citations

#natural language process... Preprint Aug 2026

CamoDocs: A Poisoning Attack Against Retrieval-Augmented Language Models Using Camouflaged Documents

CamoDocs is proposed, a poisoning attack that avoids direct query inclusion by camouflaging adversarial documents among benign content, and shows that erasure-heavy clustering defenses such as TrustRAG can reduce ASR, but only with substantial utility drops on retrieval-dependent benchmarks such as NeoQA.

Jaewon Jung, Hai-Zhong Zheng, Hongsun Jang et al. · 1 citation

#artificial intelligence Preprint Aug 2026

Beyond Confidence: Test-Time Scaling for Multi-Turn Search Agents via Retrieval Grounding

Retrieval-Grounded Voting (RGV), which scores each rollout by the lexical overlap between its final answer and the documents it retrieved, consistently outperforms confidence-based voting and identifies the underlying failure reason as copy inflation.

Hyunho Kook, Junhyuk So, Tianyu Fu et al. · 0 citations