2 papers
cs.CV2026
Capacity Overflow: A Blind Spot for Backdoor Attacks in Vision MoE
Xiaocheng Zou, Tiancheng Zheng, Xiaolin Xu +1
Mixture-of-Experts (MoE) has become a prevalent paradigm for scaling Vision Transformers efficiently. To ensure computational scalability and prevent expert overload, Vision MoE ar…
cs.CL2026
Groundhog Bit-Flip Attack: Seeding Infinite Generation Loops in Mixture-of-Experts LLMs through Bit Flips
Huakang Lin, Tiancheng Zheng, Mingxuan Sun +4
Mixture-of-Experts (MoE) architectures enable scalable and efficient large language models (LLMs) by selectively activating expert sub-networks through a routing mechanism. However…