Moral Combat: Exploiting Moral Foundations Theory to Jailbreak LLMs
cs.CL, cs.CY
Submitted: 2026-10-14
Updated: 2026-10-14
Comments: 17 pages, 6 figures
Code: https://github.com/patrickrchao/JailbreakingLLMs
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Phi-4 Technical Report
- Jailbreaking Black Box Large Language Models in Twenty Queries
- The Convergent Ethics of AI? Analyzing Moral Foundation Priorities in Large Language Models with a Multi-Framework Approach
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Machine Psychology
- Aligning AI With Shared Human Values
- DeepInception: Hypnotize Large Language Model to Be Jailbreaker
- DeepSeek-V3 Technical Report
- HarmNet: A Framework for Adaptive Multi-Turn Jailbreak Attacks on Large Language Models
- X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents
- Large Language Models Do Not Simulate Human Psychology
- Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation
- The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search
- Foot-In-The-Door: A Multi-turn Jailbreak for LLMs
- Chain of Attack: a Semantic-Driven Contextual Multi-Turn attacker for LLM
- Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement
- Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation
- Universal and Transferable Adversarial Attacks on Aligned Language Models
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