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cs.AI2026

JailbreakSkill: Scaling Automated Red-Teaming with Reusable and Ever-Evolving Skills

Xiaoyu Wen, Jiajia Li, Zhida He +11

Automated red-teaming has produced a growing collection of attack strategies, yet they typically remain scattered across prompts and workflows, making them difficult to systematica…

cs.AI2026

AgentSchool: An LLM-Powered Multi-Agent Simulation for Education

Yulei Ye, Wenhao Li, Zhong Wen +23

Despite the rapid deployment of LLMs into classrooms, validating educational AI remains uniquely intractable: interventions act on developing learners whose cognitive and social tr…

cs.AI2026

Not All Turns Matter: Credit Assignment for Multi-Turn Jailbreaking

Zhida He, Xiaoyu Wen, Han Qi +7

Deploying LLMs in multi-turn dialogues facilitates jailbreak attacks that distribute harmful intent across seemingly benign turns. Recent training-based multi-turn jailbreak method…

cs.AI2026

MAGIC: A Co-Evolving Attacker-Defender Adversarial Game for Robust LLM Safety

Xiaoyu Wen, Zhida He, Han Qi +7

Ensuring robust safety alignment is crucial for Large Language Models (LLMs), yet existing defenses often lag behind evolving adversarial attacks due to their \textbf{reliance on s…

cs.AI2025

SafeWork-R1: Coevolving Safety and Intelligence under the AI-45 Law

Shanghai AI Lab, :, Yicheng Bao +115

We introduce SafeWork-R1, a cutting-edge multimodal reasoning model that demonstrates the coevolution of capabilities and safety. It is developed by our proposed SafeLadder framewo…

cs.AI2025

The Policy Cliff: A Theoretical Analysis of Reward-Policy Maps in Large Language Models

Xingcheng Xu

Reinforcement learning (RL) plays a crucial role in shaping the behavior of large language and reasoning models (LLMs/LRMs). However, it often produces brittle and unstable policie…