3 papers
cs.LG2026
Dynamic Adversarial Reinforcement Learning for Robust Multimodal Large Language Models
Yicheng Bao, Xuhong Wang, Qiaosheng Zhang +3
Despite their impressive capabilities, Multimodal Large Language Models (MLLMs) exhibit perceptual fragility when confronted with visually complex scenes. This weakness stems from…
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.CL2026
KALE: Enhancing Knowledge Manipulation in Large Language Models via Knowledge-aware Learning
Qitan Lv, Tianyu Liu, Qiaosheng Zhang +2
Despite the impressive performance of large language models (LLMs) pretrained on vast knowledge corpora, advancing their knowledge manipulation-the ability to effectively recall, r…