Mozhdeh Rouhsedaghat — accepted AI-conference papers

2023

MAGIC: Mask-Guided Image Synthesis by Inverting a Quasi-robust Classifier

Mozhdeh Rouhsedaghat, Masoud Monajatipoor, C.-C. Jay Kuo, Iacopo Masi

AAAI 2023technical

We offer a method for one-shot mask-guided image synthesis that allows controlling manipulations of a single image by inverting a quasi-robust classifier equipped with strong regularizers. Our proposed method, entitled MAGIC, leverages structured gradients from a pre-trained quasi-robust classifier…

Cited by 6 Source ↗PDF ↗code ↗Scholar ↗

2023

MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models

Masoud Monajatipoor, Liunian Harold Li, Mozhdeh Rouhsedaghat, Lin Yang, Kai-Wei Chang

ACL 2023short

Large-scale language models have shown the ability to adapt to a new task via conditioning on a few demonstrations (i.e., in-context learning). However, in the vision-language domain, most large-scale pre-trained vision-language (VL) models do not possess the ability to conduct in-context learning.…

Cited by 19 Source ↗PDF ↗code ↗Scholar ↗