Lifelong Safety Alignment for Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Haoyu, Qin, Zeyu, Zhao, Yifei, Du, Chao, Lin, Min, Wang, Xueqian, Pang, Tianyu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
by: Zheng, Xiaosen, et al.
Published: (2024)
by: Zheng, Xiaosen, et al.
Published: (2024)
Improving Your Model Ranking on Chatbot Arena by Vote Rigging
by: Min, Rui, et al.
Published: (2025)
by: Min, Rui, et al.
Published: (2025)
Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates
by: Zheng, Xiaosen, et al.
Published: (2024)
by: Zheng, Xiaosen, et al.
Published: (2024)
Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
by: Wei, Zeming, et al.
Published: (2023)
by: Wei, Zeming, et al.
Published: (2023)
Probing the Robustness of Large Language Models Safety to Latent Perturbations
by: Gu, Tianle, et al.
Published: (2025)
by: Gu, Tianle, et al.
Published: (2025)
Safety Alignment Can Be Not Superficial With Explicit Safety Signals
by: Li, Jianwei, et al.
Published: (2025)
by: Li, Jianwei, et al.
Published: (2025)
SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models
by: Li, Lijun, et al.
Published: (2024)
by: Li, Lijun, et al.
Published: (2024)
On the Role of Attention Heads in Large Language Model Safety
by: Zhou, Zhenhong, et al.
Published: (2024)
by: Zhou, Zhenhong, et al.
Published: (2024)
Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
by: Liu, Guozhi, et al.
Published: (2025)
by: Liu, Guozhi, et al.
Published: (2025)
Exposing LLM Safety Gaps Through Mathematical Encoding:New Attacks and Systematic Analysis
by: Zhang, Haoyu, et al.
Published: (2026)
by: Zhang, Haoyu, et al.
Published: (2026)
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense
by: Min, Rui, et al.
Published: (2024)
by: Min, Rui, et al.
Published: (2024)
Instructional Fingerprinting of Large Language Models
by: Xu, Jiashu, et al.
Published: (2024)
by: Xu, Jiashu, et al.
Published: (2024)
RASA: Routing-Aware Safety Alignment for Mixture-of-Experts Models
by: Liang, Jiacheng, et al.
Published: (2026)
by: Liang, Jiacheng, et al.
Published: (2026)
Unlearned but Not Forgotten: Data Extraction after Exact Unlearning in LLM
by: Wu, Xiaoyu, et al.
Published: (2025)
by: Wu, Xiaoyu, et al.
Published: (2025)
DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models
by: Liu, Yanming, et al.
Published: (2024)
by: Liu, Yanming, et al.
Published: (2024)
Probing the Safety Response Boundary of Large Language Models via Unsafe Decoding Path Generation
by: Wang, Haoyu, et al.
Published: (2024)
by: Wang, Haoyu, et al.
Published: (2024)
Improved Techniques for Optimization-Based Jailbreaking on Large Language Models
by: Jia, Xiaojun, et al.
Published: (2024)
by: Jia, Xiaojun, et al.
Published: (2024)
Imperceptible Jailbreaking against Large Language Models
by: Gao, Kuofeng, et al.
Published: (2025)
by: Gao, Kuofeng, et al.
Published: (2025)
Machine Unlearning of Pre-trained Large Language Models
by: Yao, Jin, et al.
Published: (2024)
by: Yao, Jin, et al.
Published: (2024)
Textual Unlearning Gives a False Sense of Unlearning
by: Du, Jiacheng, et al.
Published: (2024)
by: Du, Jiacheng, et al.
Published: (2024)
DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints
by: Zhao, Andrew, et al.
Published: (2024)
by: Zhao, Andrew, et al.
Published: (2024)
Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs
by: Fonseca, Joao, et al.
Published: (2025)
by: Fonseca, Joao, et al.
Published: (2025)
Superficial Safety Alignment Hypothesis
by: Li, Jianwei, et al.
Published: (2024)
by: Li, Jianwei, et al.
Published: (2024)
LLMs can be Dangerous Reasoners: Analyzing-based Jailbreak Attack on Large Language Models
by: Lin, Shi, et al.
Published: (2024)
by: Lin, Shi, et al.
Published: (2024)
BadAgent: Inserting and Activating Backdoor Attacks in LLM Agents
by: Wang, Yifei, et al.
Published: (2024)
by: Wang, Yifei, et al.
Published: (2024)
The Task Shield: Enforcing Task Alignment to Defend Against Indirect Prompt Injection in LLM Agents
by: Jia, Feiran, et al.
Published: (2024)
by: Jia, Feiran, et al.
Published: (2024)
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models
by: Xu, Xiaoyu, et al.
Published: (2025)
by: Xu, Xiaoyu, et al.
Published: (2025)
MEUV: Achieving Fine-Grained Capability Activation in Large Language Models via Mutually Exclusive Unlock Vectors
by: Tong, Xin, et al.
Published: (2025)
by: Tong, Xin, et al.
Published: (2025)
Knowing without Acting: The Disentangled Geometry of Safety Mechanisms in Large Language Models
by: Wu, Jinman, et al.
Published: (2026)
by: Wu, Jinman, et al.
Published: (2026)
EnJa: Ensemble Jailbreak on Large Language Models
by: Zhang, Jiahao, et al.
Published: (2024)
by: Zhang, Jiahao, et al.
Published: (2024)
Securing Multi-turn Conversational Language Models From Distributed Backdoor Triggers
by: Tong, Terry, et al.
Published: (2024)
by: Tong, Terry, et al.
Published: (2024)
Uncovering Logit Suppression Vulnerabilities in LLM Safety Alignment
by: Li, Yuxi, et al.
Published: (2024)
by: Li, Yuxi, et al.
Published: (2024)
A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
by: Wang, Kun, et al.
Published: (2025)
by: Wang, Kun, et al.
Published: (2025)
Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable
by: Huang, Tiansheng, et al.
Published: (2025)
by: Huang, Tiansheng, et al.
Published: (2025)
Extracting Training Data from Diffusion Language Models via Infilling
by: Wang, Yihan, et al.
Published: (2026)
by: Wang, Yihan, et al.
Published: (2026)
Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM
by: Cao, Bochuan, et al.
Published: (2023)
by: Cao, Bochuan, et al.
Published: (2023)
Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval
by: Chen, Taiye, et al.
Published: (2025)
by: Chen, Taiye, et al.
Published: (2025)
Directional Embedding Smoothing for Robust Vision Language Models
by: Wang, Ye, et al.
Published: (2026)
by: Wang, Ye, et al.
Published: (2026)
In Vino Veritas and Vulnerabilities: Examining LLM Safety via Drunk Language Inducement
by: Shetty, Anudeex, et al.
Published: (2026)
by: Shetty, Anudeex, et al.
Published: (2026)
The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs
by: Chen, Bocheng, et al.
Published: (2024)
by: Chen, Bocheng, et al.
Published: (2024)
Similar Items
-
Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses
by: Zheng, Xiaosen, et al.
Published: (2024) -
Improving Your Model Ranking on Chatbot Arena by Vote Rigging
by: Min, Rui, et al.
Published: (2025) -
Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates
by: Zheng, Xiaosen, et al.
Published: (2024) -
Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
by: Wei, Zeming, et al.
Published: (2023) -
Probing the Robustness of Large Language Models Safety to Latent Perturbations
by: Gu, Tianle, et al.
Published: (2025)