Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component in our daily lives, providing …
have become an indispensable and important component in our daily lives, providing …
A pathway towards responsible ai generated content
AI Generated Content (AIGC) has received tremendous attention within the past few years,
with content generated in the format of image, text, audio, video, etc. Meanwhile, AIGC has …
with content generated in the format of image, text, audio, video, etc. Meanwhile, AIGC has …
Is heterogeneity notorious? taming heterogeneity to handle test-time shift in federated learning
Federated learning (FL) is an effective machine learning paradigm where multiple clients
can train models based on heterogeneous data in a decentralized manner without …
can train models based on heterogeneous data in a decentralized manner without …
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 …
Foundation model for advancing healthcare: Challenges, opportunities, and future directions
Foundation model, which is pre-trained on broad data and is able to adapt to a wide range
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …
How to detect unauthorized data usages in text-to-image diffusion models
Recent text-to-image diffusion models have shown surprising performance in generating
high-quality images. However, concerns have arisen regarding the unauthorized usage of …
high-quality images. However, concerns have arisen regarding the unauthorized usage of …
Federated fine-tuning of billion-sized language models across mobile devices
Large Language Models (LLMs) are transforming the landscape of mobile intelligence.
Federated Learning (FL), a method to preserve user data privacy, is often employed in fine …
Federated Learning (FL), a method to preserve user data privacy, is often employed in fine …
ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning
When personalized federated learning (FL) meets large foundation models, new challenges
arise from various limitations in resources. In addition to typical limitations such as data …
arise from various limitations in resources. In addition to typical limitations such as data …
Backdoor threats from compromised foundation models to federated learning
Federated learning (FL) represents a novel paradigm to machine learning, addressing
critical issues related to data privacy and security, yet suffering from data insufficiency and …
critical issues related to data privacy and security, yet suffering from data insufficiency and …
Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark
Federated learning has emerged as a promising paradigm for privacy-preserving
collaboration among different parties. Recently, with the popularity of federated learning, an …
collaboration among different parties. Recently, with the popularity of federated learning, an …