Federation over Text: Insight Sharing for Multi-Agent Reasoning

Excerpt

arXiv:2604.16778v3 Announce Type: replace Abstract: Modern agents specialize in varying domains while there is no clear approach combining different domain skills. We propose a federated learning-like framework, Federation over Text (FoT), that enables multiple clients solving different tasks to collectively generate a shared library of metacognitive insights by iteratively federating their local reasoning processes without sharing actual problem instances. Instead of federation over gradients (