2 citations · 7 across the 13 of their papers we have counts for
5 papers · 1 filter
Dual Prototype Evolving for Test-Time Generalization of Vision-Language Models
Ce Zhang, Simon Stepputtis, Katia Sycara +1
Test-time adaptation, which enables models to generalize to diverse data with unlabeled test samples, holds significant value in real-world scenarios. Recently, researchers have ap…
HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation
Ce Zhang, Simon Stepputtis, Joseph Campbell +2
Being able to understand visual scenes is a precursor for many downstream tasks, including autonomous driving, robotics, and other vision-based approaches. A common approach enabli…
Test-time Distribution Learning Adapter for Cross-modal Visual Reasoning
Yi Zhang, Ce Zhang
Vision-Language Pre-Trained (VLP) models, such as CLIP, have demonstrated remarkable effectiveness in learning generic visual representations. Several approaches aim to efficiently…
Enhancing Vision-Language Few-Shot Adaptation with Negative Learning
Ce Zhang, Simon Stepputtis, Katia Sycara +1
Large-scale pre-trained Vision-Language Models (VLMs) have exhibited impressive zero-shot performance and transferability, allowing them to adapt to downstream tasks in a data-effi…
Concept-Guided Prompt Learning for Generalization in Vision-Language Models
Yi Zhang, Ce Zhang, Ke Yu +2
Contrastive Language-Image Pretraining (CLIP) model has exhibited remarkable efficacy in establishing cross-modal connections between texts and images, yielding impressive performa…