DSPrompt: Dynamic Soft Prompt Defense against M-RAG Corruption

Multimodal Retrieval Augmented Generation M-RAG is increasingly vulnerable to adversarial attacks where malicious data are crafted to produce embeddings that align with benign entries in the vector space, deceiving retrieval and inducing harmful outputs. Existing defenses primarily operate at que...

The Safety Reminder: a Soft Prompt to Reactivate Delayed Safety Awareness in Vision-Language Models

As Vision-Language Models VLMs demonstrate increasing capabilities across real-world applications such as code generation and chatbot assistance, ensuring their safety has become paramount. Unlike traditional Large Language Models LLMs, VLMs face unique vulnerabilities due to their multimodal...

SafeGenes: Evaluating the Adversarial Robustness of Genomic Foundation Models

Genomic Foundation Models GFMs, such as Evolutionary Scale Modeling ESM, have demonstrated significant success in variant effect prediction. However, their adversarial robustness remains largely unexplored. To address this gap, we propose SafeGenes: a framework for Secure analysis of genomic...