2 citations · 5 across the 5 of their papers we have counts for
5 papers
An Intermediate Fusion ViT Enables Efficient Text-Image Alignment in Diffusion Models
Zizhao Hu, Shaochong Jia, Mohammad Rostami
Diffusion models have been widely used for conditional data cross-modal generation tasks such as text-to-image and text-to-video. However, state-of-the-art models still fail to ali…
Class-Incremental Learning Using Generative Experience Replay Based on Time-aware Regularization
Zizhao Hu, Mohammad Rostami
Learning new tasks accumulatively without forgetting remains a critical challenge in continual learning. Generative experience replay addresses this challenge by synthesizing pseud…
Cognitively Inspired Cross-Modal Data Generation Using Diffusion Models
Zizhao Hu, Mohammad Rostami
Most existing cross-modal generative methods based on diffusion models use guidance to provide control over the latent space to enable conditional generation across different modal…
Encoding Binary Concepts in the Latent Space of Generative Models for Enhancing Data Representation
Zizhao Hu, Mohammad Rostami
Binary concepts are empirically used by humans to generalize efficiently. And they are based on Bernoulli distribution which is the building block of information. These concepts sp…
Evaluating NLP Systems On a Novel Cloze Task: Judging the Plausibility of Possible Fillers in Instructional Texts
Zizhao Hu, Ravikiran Chanumolu, Xingyu Lin +2
Cloze task is a widely used task to evaluate an NLP system's language understanding ability. However, most of the existing cloze tasks only require NLP systems to give the relative…