most citedTimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Creating a Lens of Chinese Culture: A Multimodal Dataset for Chinese Pun Rebus Art Understanding

Tuo Zhang, Tiantian Feng, Yibin Ni +7

Large vision-language models (VLMs) have demonstrated remarkable abilities in understanding everyday content. However, their performance in the domain of art, particularly cultural…

cs.LG2023

FedAIoT: A Federated Learning Benchmark for Artificial Intelligence of Things

Samiul Alam, Tuo Zhang, Tiantian Feng +8

There is a significant relevance of federated learning (FL) in the realm of Artificial Intelligence of Things (AIoT). However, most existing FL works do not use datasets collected…

cs.DC2023

FedMultimodal: A Benchmark For Multimodal Federated Learning

Tiantian Feng, Digbalay Bose, Tuo Zhang +6

Over the past few years, Federated Learning (FL) has become an emerging machine learning technique to tackle data privacy challenges through collaborative training. In the Federate…

cs.LG2023

GPT-FL: Generative Pre-trained Model-Assisted Federated Learning

Tuo Zhang, Tiantian Feng, Samiul Alam +5

In this work, we propose GPT-FL, a generative pre-trained model-assisted federated learning (FL) framework. At its core, GPT-FL leverages generative pre-trained models to generate…

cs.LG20233 cited

TimelyFL: Heterogeneity-aware Asynchronous Federated Learning with Adaptive Partial Training

Tuo Zhang, Lei Gao, Sunwoo Lee +2

In cross-device Federated Learning (FL) environments, scaling synchronous FL methods is challenging as stragglers hinder the training process. Moreover, the availability of each cl…