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cs.LG2025
Don't Forget the Nonlinearity: Unlocking Activation Functions in Efficient Fine-Tuning
Bo Yin, Xingyi Yang, Xinchao Wang
Existing parameter-efficient fine-tuning (PEFT) methods primarily adapt weight matrices while keeping activation functions fixed. We introduce \textbf{NoRA}, the first PEFT framewo…
cs.LG2025
GraphBridge: Towards Arbitrary Transfer Learning in GNNs
Li Ju, Xingyi Yang, Qi Li +1
Graph neural networks (GNNs) are conventionally trained on a per-domain, per-task basis. It creates a significant barrier in transferring the acquired knowledge to different, heter…
cs.LG2024★ 17 cited
Kolmogorov-Arnold Transformer
Xingyi Yang, Xinchao Wang
Transformers stand as the cornerstone of mordern deep learning. Traditionally, these models rely on multi-layer perceptron (MLP) layers to mix the information between channels. In…