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Safety Alignment

Papers

Showing 2650 of 288 papers

TitleStatusHype
Lifelong Safety Alignment for Language ModelsCode1
MPO: Multilingual Safety Alignment via Reward Gap OptimizationCode1
MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teamingCode1
Safety Subspaces are Not Distinct: A Fine-Tuning Case StudyCode1
Linear Control of Test Awareness Reveals Differential Compliance in Reasoning ModelsCode1
AdaSteer: Your Aligned LLM is Inherently an Adaptive Jailbreak DefenderCode1
VPO: Aligning Text-to-Video Generation Models with Prompt OptimizationCode1
sudo rm -rf agentic_securityCode1
LookAhead Tuning: Safer Language Models via Partial Answer PreviewsCode1
SafeMERGE: Preserving Safety Alignment in Fine-Tuned Large Language Models via Selective Layer-Wise Model MergingCode1
Improving LLM Safety Alignment with Dual-Objective OptimizationCode1
Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less ReasonableCode1
Steering Dialogue Dynamics for Robustness against Multi-turn Jailbreaking AttacksCode1
Reasoning-Augmented Conversation for Multi-Turn Jailbreak Attacks on Large Language ModelsCode1
X-Boundary: Establishing Exact Safety Boundary to Shield LLMs from Multi-Turn Jailbreaks without Compromising UsabilityCode1
QueryAttack: Jailbreaking Aligned Large Language Models Using Structured Non-natural Query LanguageCode1
Speak Easy: Eliciting Harmful Jailbreaks from LLMs with Simple InteractionsCode1
Panacea: Mitigating Harmful Fine-tuning for Large Language Models via Post-fine-tuning PerturbationCode1
xJailbreak: Representation Space Guided Reinforcement Learning for Interpretable LLM JailbreakingCode1
Autonomous Microscopy Experiments through Large Language Model AgentsCode1
PrivAgent: Agentic-based Red-teaming for LLM Privacy LeakageCode1
Immune: Improving Safety Against Jailbreaks in Multi-modal LLMs via Inference-Time AlignmentCode1
SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt TypesCode1
Bayesian scaling laws for in-context learningCode1
Locking Down the Finetuned LLMs SafetyCode1
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