Personalized Collaborative Fine-Tuning of On-Device Large Language Models to Address Data Heterogeneity and Scarcity

Personalized collaborative fine-tuning protocols can effectively address the challenges of data heterogeneity and scarcity in on-device large language model deployments, outperforming both local fine-tuning and naive averaging approaches.