activity
20242026
collaborators

7 papers

cs.CL2026

What Language Models Know But Don't Say: Non-Generative Prior Extraction for Generalization

Sara Rezaeimanesh, Mohammad M. Ghassemi, Kundan Thind +1

In domains like medicine and finance, large-scale labeled data is costly and often unavailable, leading to models trained on small datasets that struggle to generalize to real-worl…

cs.SE2025

Extracting Overlapping Microservices from Monolithic Code via Deep Semantic Embeddings and Graph Neural Network-Based Soft Clustering

Morteza Ziabakhsh, Kiyan Rezaee, Sadegh Eskandari +2

Modern software systems are increasingly shifting from monolithic architectures to microservices to enhance scalability, maintainability, and deployment flexibility. Existing micro…

cs.LG2025

MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks

Lotfi Abdelkrim Mecharbat, Alberto Marchisio, Muhammad Shafique +2

There has been a surge in optimizing edge Deep Neural Networks (DNNs) for accuracy and efficiency using traditional optimization techniques such as pruning, and more recently, empl…

cs.LG2025

Online Continual Learning: A Systematic Literature Review of Approaches, Challenges, and Benchmarks

Seyed Amir Bidaki, Amir Mohammadkhah, Kiyan Rezaee +4

Online Continual Learning (OCL) is a critical area in machine learning, focusing on enabling models to adapt to evolving data streams in real-time while addressing challenges such…

cs.CV2025

GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation

Niloufar Eghbali, Hassan Bagher-Ebadian, Tuka Alhanai +1

Vision Transformers (ViTs) have shown promise in medical image semantic segmentation (MISS) by capturing long-range correlations. However, ViTs often struggle to model local spatia…

eess.SP2024

An LSTM Feature Imitation Network for Hand Movement Recognition from sEMG Signals

Chuheng Wu, S. Farokh Atashzar, Mohammad M. Ghassemi +1

Surface Electromyography (sEMG) is a non-invasive signal that is used in the recognition of hand movement patterns, the diagnosis of diseases, and the robust control of prostheses.…