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cs.LG2026
GAST: Gradient-aligned Sparse Tuning of Large Language Models with Data-layer Selection
Kai Yao, Zhenghan Song, Kaixin Wu +5
Parameter-Efficient Fine-Tuning (PEFT) has become a key strategy for adapting large language models, with recent advances in sparse tuning reducing overhead by selectively updating…
cs.LG2025
Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning
Tiandi Ye, Wenyan Liu, Kai Yao +6
Federated learning (FL) is a privacy-preserving machine learning paradigm that enables collaborative model training across multiple distributed clients without disclosing their raw…