3 citations · 4 across the 11 of their papers we have counts for
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cs.CV2024
Decomposing the Neurons: Activation Sparsity via Mixture of Experts for Continual Test Time Adaptation
Rongyu Zhang, Aosong Cheng, Yulin Luo +8
Continual Test-Time Adaptation (CTTA), which aims to adapt the pre-trained model to ever-evolving target domains, emerges as an important task for vision models. As current vision…
cs.CV2024
Proximity QA: Unleashing the Power of Multi-Modal Large Language Models for Spatial Proximity Analysis
Jianing Li, Xi Nan, Ming Lu +2
Multi-modal large language models (MLLMs) have demonstrated remarkable vision-language capabilities, primarily due to the exceptional in-context understanding and multi-task learni…
cs.CV2024
VeCAF: Vision-language Collaborative Active Finetuning with Training Objective Awareness
Rongyu Zhang, Zefan Cai, Huanrui Yang +9
Finetuning a pretrained vision model (PVM) is a common technique for learning downstream vision tasks. However, the conventional finetuning process with randomly sampled data point…