Latest Articles for Collaborative Systems

EFVFL provides a stable method for efficient communication without sharing private data.

Introducing FedGTG to retain knowledge while learning in federated settings.

POGEMA framework enhances multi-agent navigation for efficient obstacle avoidance.

A new method improves learning efficiency while preserving knowledge in federated learning systems.

ReDel helps AI agents work together on complex tasks efficiently.

A new method improves safeguarding against attacks in federated learning systems.

A new framework enhances federated learning by addressing noisy data issues.

A new approach enhances teamwork and decision-making in decentralized robot systems.

A novel approach to safeguard sensitive data through collaborative encryption methods.

A new method enhances federated learning's security by combating Byzantine attacks effectively.

RoLoRA enhances federated learning with robust fine-tuning and efficient communication.

A new approach to improve AI reasoning using multi-agent strategies.

Selective encryption enhances privacy while maintaining model performance in collaborative learning.

A-FedPD aligns model updates to reduce training instability in federated learning.

A look at federated learning's challenges and solutions in maintaining data privacy and model accuracy.

HEXA-MoE improves AI efficiency with expert collaboration and reduced communication.

Discover how Safe RL ensures smarter and safer AI interactions.

FedGR improves federated learning by refining noisy labels for better collaboration.

Discover how MALT enhances problem-solving through teamwork among language models.

Combining personalized models with global insights for enhanced privacy in data sharing.

FedPIA enhances machine learning while safeguarding sensitive data privacy.

Robots learn to walk together using advanced methods without sharing sensitive data.

Calibre enhances personalized federated learning with better model performance and fairness.