19 citations · 29 across the 10 of their papers we have counts for
4 papers · 1 filter
Learning to Rank Pre-trained Vision-Language Models for Downstream Tasks
Yuhe Ding, Bo Jiang, Aihua Zheng +2
Vision language models (VLMs) like CLIP show stellar zero-shot capability on classification benchmarks. However, selecting the VLM with the highest performance on the unlabeled dow…
State Space Model for New-Generation Network Alternative to Transformers: A Survey
Xiao Wang, Shiao Wang, Yuhe Ding +13
In the post-deep learning era, the Transformer architecture has demonstrated its powerful performance across pre-trained big models and various downstream tasks. However, the enorm…
Which Model to Transfer? A Survey on Transferability Estimation
Yuhe Ding, Bo Jiang, Aijing Yu +2
Transfer learning methods endeavor to leverage relevant knowledge from existing source pre-trained models or datasets to solve downstream target tasks. With the increase in the sca…
Exploring Vacant Classes in Label-Skewed Federated Learning
Kuangpu Guo, Yuhe Ding, Jian Liang +3
Label skews, characterized by disparities in local label distribution across clients, pose a significant challenge in federated learning. As minority classes suffer from worse accu…