When Saying ‘No’ Isn’t Enough: Hardening Language Models Against Jailbreaks
New research reveals a critical flaw in current AI safety protocols – a tendency for models to override safety features when pressured – and proposes a more robust approach to prevent unintended outputs.



![Vision Mamba proposes a selective state space model-a departure from traditional transformers-that utilizes a hardware-aware, temporally selective scan to process visual inputs, achieving a linear scaling in sequence length and promising improved efficiency in vision tasks through a principled reduction of computational redundancy inherent in attention mechanisms [latex]O(N) [/latex] versus [latex]O(N^2)[/latex].](https://arxiv.org/html/2602.16723v1/Fig/visionMamba.jpg)




