5 papers
Counterfactual Reasoning for Fine-Grained Evidence Disentanglement in VideoQA
Zhou Du, Hamid Krim, Xiao Wu +3
Recent advances in video multimodal models have significantly improved VideoQA performance. However, these systems often rely on spurious statistical correlations rather than answe…
ViTCAE: ViT-based Class-conditioned Autoencoder
Vahid Jebraeeli, Hamid Krim, Derya Cansever
Vision Transformer (ViT) based autoencoders often underutilize the global Class token and employ static attention mechanisms, limiting both generative control and optimization effi…
Boosting Adversarial Robustness and Generalization with Structural Prior
Zhichao Hou, Weizhi Gao, Hamid Krim +1
This work investigates a novel approach to boost adversarial robustness and generalization by incorporating structural prior into the design of deep learning models. Specifically,…
Robustness Reprogramming for Representation Learning
Zhichao Hou, MohamadAli Torkamani, Hamid Krim +1
This work tackles an intriguing and fundamental open challenge in representation learning: Given a well-trained deep learning model, can it be reprogrammed to enhance its robustnes…
Generative Expansion of Small Datasets: An Expansive Graph Approach
Vahid Jebraeeli, Bo Jiang, Hamid Krim +1
Limited data availability in machine learning significantly impacts performance and generalization. Traditional augmentation methods enhance moderately sufficient datasets. GANs st…