Distributed LLMs stop treating bias as a local defect: nodes swap a 3D bias state, cutting inter-node variance by about 87% in a pilot
Distributed LLMs can treat bias as a network state that evolves with communication: nodes exchange a three-dimensional bias state and align by consensus, cutting composite bias by about 48.5% and inter-node bias-state variance by about 87.4% versus FedAvg in a lightweight Transformer pilot.