10 citations · 13 across the 6 of their papers we have counts for
6 papers
Fine-Grained Erasure in Text-to-Image Diffusion-based Foundation Models
Kartik Thakral, Tamar Glaser, Tal Hassner +2
Existing unlearning algorithms in text-to-image generative models often fail to preserve the knowledge of semantically related concepts when removing specific target concepts: a ch…
Continual Unlearning for Foundational Text-to-Image Models without Generalization Erosion
Kartik Thakral, Tamar Glaser, Tal Hassner +2
How can we effectively unlearn selected concepts from pre-trained generative foundation models without resorting to extensive retraining? This research introduces `continual unlear…
Navigating Text-to-Image Generative Bias across Indic Languages
Surbhi Mittal, Arnav Sudan, Mayank Vatsa +3
This research investigates biases in text-to-image (TTI) models for the Indic languages widely spoken across India. It evaluates and compares the generative performance and cultura…
HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings
Nikhil Mehta, Kevin J Liang, Jing Huang +3
Out-of-distribution (OOD) detection is an important topic for real-world machine learning systems, but settings with limited in-distribution samples have been underexplored. Such f…
On Responsible Machine Learning Datasets with Fairness, Privacy, and Regulatory Norms
Surbhi Mittal, Kartik Thakral, Richa Singh +4
Artificial Intelligence (AI) has made its way into various scientific fields, providing astonishing improvements over existing algorithms for a wide variety of tasks. In recent yea…
Effective Face Frontalization in Unconstrained Images
Tal Hassner, Shai Harel, Eran Paz +1
"Frontalization" is the process of synthesizing frontal facing views of faces appearing in single unconstrained photos. Recent reports have suggested that this process may substant…