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cs.CR2026
TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts
Hua-Rong Chu, Kuan-Chun Wang, Yao-Te Huang
Safety guardrails have become an active area of research in AI safety, aimed at ensuring the appropriate behavior of large language models (LLMs). However, existing research lacks…
cs.CR2025
Never compromise with vulnerabilities: a comprehensive survey on AI governance
Yuchu Jiang, Jian Zhao, Yuchen Yuan +62
The rapid advancement of AI has expanded its capabilities across domains, yet introduced critical technical vulnerabilities, such as algorithmic bias and adversarial sensitivity, t…
cs.CR2025
Breaking the Ceiling: Exploring the Potential of Jailbreak Attacks through Expanding Strategy Space
Yao Huang, Yitong Sun, Shouwei Ruan +3
Large Language Models (LLMs), despite advanced general capabilities, still suffer from numerous safety risks, especially jailbreak attacks that bypass safety protocols. Understandi…