4 papers
Scenes as an Attack Surface: Uncovering Scene-Grounded Safety Failures in MLLMs
Tongxi Wu, Yuyang Cheng, Jiacheng Xian +5
Existing jailbreak attacks have exposed serious safety weaknesses in multimodal large language models (MLLMs). Most prior attacks rely on specially constructed visual inputs to car…
Furina: Fragmented Uncertainty-Driven Refusal Instability Attack
Tongxi Wu, Jian Zhang, Yang Gao
Safety alignment in large language models (LLMs) and multimodal large language models (MLLMs) is commonly assumed to operate as a near-binary threshold mechanism. We challenge this…
The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence
Aili Chen, Aonian Li, Baichuan Zhou +215
We introduce the MiniMax-M2 series, a family of Mixture-of-Experts language models built around the principle that mini activations can unleash maximum real-world intelligence. The…
MedForge: Interpretable Medical Deepfake Detection via Forgery-aware Reasoning
Zhihui Chen, Kai He, Qingyuan Lei +4
Text-guided image editors can now manipulate authentic medical scans with high fidelity, enabling lesion implantation/removal that threatens clinical trust and safety. Existing def…