436 citations · 1.4k across the 41 of their papers we have counts for
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Differentially Private Representation Learning via Image Captioning
Tom Sander, Yaodong Yu, Maziar Sanjabi +4
Differentially private (DP) machine learning is considered the gold-standard solution for training a model from sensitive data while still preserving privacy. However, a major barr…
Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression
Animesh Sinha, Bo Sun, Anmol Kalia +14
We introduce Style Tailoring, a recipe to finetune Latent Diffusion Models (LDMs) in a distinct domain with high visual quality, prompt alignment and scene diversity. We choose sti…
EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods
Samyadeep Basu, Mehrdad Saberi, Shweta Bhardwaj +5
A plethora of text-guided image editing methods have recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models such as Imag…
Identifying Interpretable Subspaces in Image Representations
Neha Kalibhat, Shweta Bhardwaj, Bayan Bruss +3
We propose Automatic Feature Explanation using Contrasting Concepts (FALCON), an interpretability framework to explain features of image representations. For a target feature, FALC…
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP
Samyadeep Basu, Shell Xu Hu, Maziar Sanjabi +2
Image-text contrastive models like CLIP have wide applications in zero-shot classification, image-text retrieval, and transfer learning. However, they often struggle on composition…
ViP: A Differentially Private Foundation Model for Computer Vision
Yaodong Yu, Maziar Sanjabi, Yi Ma +2
Artificial intelligence (AI) has seen a tremendous surge in capabilities thanks to the use of foundation models trained on internet-scale data. On the flip side, the uncurated natu…
Text-To-Concept (and Back) via Cross-Model Alignment
Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi +1
We observe that the mapping between an image's representation in one model to its representation in another can be learned surprisingly well with just a linear layer, even across d…
Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning
Ajinkya Tejankar, Maziar Sanjabi, Qifan Wang +4
Recently, self-supervised learning (SSL) was shown to be vulnerable to patch-based data poisoning backdoor attacks. It was shown that an adversary can poison a small part of the un…
MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding
Woojeong Jin, Maziar Sanjabi, Shaoliang Nie +3
To reduce a model size but retain performance, we often rely on knowledge distillation (KD) which transfers knowledge from a large "teacher" model to a smaller "student" model. How…