6 citations · 11 across the 6 of their papers we have counts for
3 papers · 1 filter
Robustness in Both Domains: CLIP Needs a Robust Text Encoder
Elias Abad Rocamora, Christian Schlarmann, Naman Deep Singh +3
Adversarial input attacks can cause a significant shift of CLIP embeddings. This can affect the downstream robustness of models incorporating CLIP in the pipeline, such as text-to-…
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
Christian Schlarmann, Naman Deep Singh, Francesco Croce +1
Multi-modal foundation models like OpenFlamingo, LLaVA, and GPT-4 are increasingly used for various real-world tasks. Prior work has shown that these models are highly vulnerable t…
On the Adversarial Robustness of Multi-Modal Foundation Models
Christian Schlarmann, Matthias Hein
Multi-modal foundation models combining vision and language models such as Flamingo or GPT-4 have recently gained enormous interest. Alignment of foundation models is used to preve…