2 papers
cs.DC2025
Unity is Power: Semi-Asynchronous Collaborative Training of Large-Scale Models with Structured Pruning in Resource-Limited Clients
Yan Li, Xiao Zhang, Mingyi Li +7
In this work, we study to release the potential of massive heterogeneous weak computing power to collaboratively train large-scale models on dispersed datasets. In order to improve…
cs.MA2025
PE-MA: Parameter-Efficient Co-Evolution of Multi-Agent Systems
Yingfan Deng, Anhao Zhou, Yuan Yuan +3
Multi-Agent Systems have recently emerged as a promising paradigm for collaborative reasoning and solving complex tasks. However, the design of collaborative learning algorithms in…