Shang-Hao Wu

Communication-efficient heterogeneous federated learning for large language models: federated asymmetric adaptive LoRA fine-tuning

The Federated Asymmetric Adaptive LoRA method reduces trainable parameters by nearly half compared with standard AdaLoRA, while incurring only a marginal performance degradation, and introduces the Federated Adaptive Budget Strategy to enhance the effectiveness of federated learning.