13 citations · 19 across the 6 of their papers we have counts for
6 papers
Jigsaw Game: Federated Clustering
Jinxuan Xu, Hong-You Chen, Wei-Lun Chao +1
Federated learning has recently garnered significant attention, especially within the domain of supervised learning. However, despite the abundance of unlabeled data on end-users,…
SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models
Mingze Xu, Mingfei Gao, Zhe Gan +5
We propose SlowFast-LLaVA (or SF-LLaVA for short), a training-free video large language model (LLM) that can jointly capture detailed spatial semantics and long-range temporal cont…
Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models
Haotian Zhang, Haoxuan You, Philipp Dufter +8
While Ferret seamlessly integrates regional understanding into the Large Language Model (LLM) to facilitate its referring and grounding capability, it poses certain limitations: co…
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
Cheng-Hao Tu, Hong-You Chen, Zheda Mai +7
We propose a learning problem involving adapting a pre-trained source model to the target domain for classifying all classes that appeared in the source data, using target data tha…
Learning Fractals by Gradient Descent
Cheng-Hao Tu, Hong-You Chen, David Carlyn +1
Fractals are geometric shapes that can display complex and self-similar patterns found in nature (e.g., clouds and plants). Recent works in visual recognition have leveraged this p…
Gradual Domain Adaptation without Indexed Intermediate Domains
Hong-You Chen, Wei-Lun Chao
The effectiveness of unsupervised domain adaptation degrades when there is a large discrepancy between the source and target domains. Gradual domain adaptation (GDA) is one promisi…