14 citations · 42 across the 7 of their papers we have counts for
9 papers
LLMs in Biomedicine: A study on clinical Named Entity Recognition
Masoud Monajatipoor, Jiaxin Yang, Joel Stremmel +4
Large Language Models (LLMs) demonstrate remarkable versatility in various NLP tasks but encounter distinct challenges in biomedical due to the complexities of language and data sc…
MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models
Masoud Monajatipoor, Liunian Harold Li, Mozhdeh Rouhsedaghat +2
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 doma…
MAGIC: Mask-Guided Image Synthesis by Inverting a Quasi-Robust Classifier
Mozhdeh Rouhsedaghat, Masoud Monajatipoor, C. -C. Jay Kuo +1
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 regul…
BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis
Masoud Monajatipoor, Mozhdeh Rouhsedaghat, Liunian Harold Li +4
Vision-and-language(V&L) models take image and text as input and learn to capture the associations between them. Prior studies show that pre-trained V&L models can significantly im…
DefakeHop: A Light-Weight High-Performance Deepfake Detector
Hong-Shuo Chen, Mozhdeh Rouhsedaghat, Hamza Ghani +3
A light-weight high-performance Deepfake detection method, called DefakeHop, is proposed in this work. State-of-the-art Deepfake detection methods are built upon deep neural networ…
Successive Subspace Learning: An Overview
Mozhdeh Rouhsedaghat, Masoud Monajatipoor, Zohreh Azizi +1
Successive Subspace Learning (SSL) offers a light-weight unsupervised feature learning method based on inherent statistical properties of data units (e.g. image pixels and points i…
Low-Resolution Face Recognition In Resource-Constrained Environments
Mozhdeh Rouhsedaghat, Yifan Wang, Shuowen Hu +2
A non-parametric low-resolution face recognition model for resource-constrained environments with limited networking and computing is proposed in this work. Such environments often…
FaceHop: A Light-Weight Low-Resolution Face Gender Classification Method
Mozhdeh Rouhsedaghat, Yifan Wang, Xiou Ge +3
A light-weight low-resolution face gender classification method, called FaceHop, is proposed in this research. We have witnessed rapid progress in face gender classification accura…
PixelHop++: A Small Successive-Subspace-Learning-Based (SSL-based) Model for Image Classification
Yueru Chen, Mozhdeh Rouhsedaghat, Suya You +2
The successive subspace learning (SSL) principle was developed and used to design an interpretable learning model, known as the PixelHop method,for image classification in our prio…