EOPSA: Efficient On-Policy Self-Distilled Safety Alignment
cs.AI
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/neuqrui/EOPSA
Terminology
Sources
- Evaluating Large Language Models Trained on Code
- Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
- Reducing the Safety Tax in LLM Safety Alignment with On-Policy Self-Distillation
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable
- R1-ACT: Efficient Reasoning Model Safety Alignment by Activating Safety Knowledge
- Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
- OpenAI o1 System Card
- Reasoning as an Adaptive Defense for Safety
- THINKSAFE: Self-Generated Safety Alignment for Reasoning Models
- HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
- GPQA: A Graduate-Level Google-Proof Q&A Benchmark
- Proximal Policy Optimization Algorithms
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Kimi K2: Open Agentic Intelligence
- ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming
- Safety in Large Reasoning Models: A Survey
- STAR-1: Safer Alignment of Reasoning LLMs with 1K Data
- Constitutional On-Policy Safe Distillation
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