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Found 4 papers, 3 papers with code
FwdLLM: Efficient FedLLM using Forward Gradient
Federated Learning (FL), a method to preserve user data privacy, is often employed in fine-tuning LLMs to downstream mobile tasks, an approach known as FedLLM.
Federated Few-Shot Learning for Mobile NLP
Such an inadequacy of data labels is known as a few-shot scenario; it becomes the key blocker for mobile NLP applications.
Towards Practical Few-shot Federated NLP
To address these challenges, we first introduce a data generator for federated few-shot learning tasks, which encompasses the quantity and skewness of scarce labeled data in a realistic setting.
FedAdapter: Efficient Federated Learning for Modern NLP
A key challenge is to properly configure the depth and width of adapters, to which the training speed and efficiency is highly sensitive.
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