Multimodal federated learning: A survey
Federated learning (FL), which provides a collaborative training scheme for distributed data
sources with privacy concerns, has become a burgeoning and attractive research area. Most …
sources with privacy concerns, has become a burgeoning and attractive research area. Most …
An HCI-Centric Survey and Taxonomy of Human-Generative-AI Interactions
Generative AI (GenAI) has shown remarkable capabilities in generating diverse and realistic
content across different formats like images, videos, and text. In Generative AI, human …
content across different formats like images, videos, and text. In Generative AI, human …
Faithful vision-language interpretation via concept bottleneck models
The demand for transparency in healthcare and finance has led to interpretable machine
learning (IML) models, notably the concept bottleneck models (CBMs), valued for their …
learning (IML) models, notably the concept bottleneck models (CBMs), valued for their …
Feddat: An approach for foundation model finetuning in multi-modal heterogeneous federated learning
Recently, foundation models have exhibited remarkable advancements in multi-modal
learning. These models, equipped with millions (or billions) of parameters, typically require a …
learning. These models, equipped with millions (or billions) of parameters, typically require a …
A review of machine learning and deep learning for object detection, semantic segmentation, and human action recognition in machine and robotic vision
Machine vision, an interdisciplinary field that aims to replicate human visual perception in
computers, has experienced rapid progress and significant contributions. This paper traces …
computers, has experienced rapid progress and significant contributions. This paper traces …
Global and local prompts cooperation via optimal transport for federated learning
Prompt learning in pretrained visual-language models has shown remarkable flexibility
across various downstream tasks. Leveraging its inherent lightweight nature recent research …
across various downstream tasks. Leveraging its inherent lightweight nature recent research …
Federated text-driven prompt generation for vision-language models
C Qiu, X Li, CK Mummadi, MR Ganesh, Z Li… - The Twelfth …, 2024 - openreview.net
Prompt learning for vision-language models, eg, CoOp, has shown great success in
adapting CLIP to different downstream tasks, making it a promising solution for federated …
adapting CLIP to different downstream tasks, making it a promising solution for federated …
Text-driven prompt generation for vision-language models in federated learning
Prompt learning for vision-language models, eg, CoOp, has shown great success in
adapting CLIP to different downstream tasks, making it a promising solution for federated …
adapting CLIP to different downstream tasks, making it a promising solution for federated …
Learning personalized causally invariant representations for heterogeneous federated clients
Personalized federated learning (PFL) has gained great success in tackling the scenarios
where target datasets are heterogeneous across the local clients. However, the application …
where target datasets are heterogeneous across the local clients. However, the application …
Flora: Enhancing vision-language models with parameter-efficient federated learning
In the rapidly evolving field of artificial intelligence, multimodal models, eg, integrating vision
and language into visual-language models (VLMs), have become pivotal for many …
and language into visual-language models (VLMs), have become pivotal for many …