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cs.LG2025
Revisiting LoRA through the Lens of Parameter Redundancy: Spectral Encoding Helps
Jiashun Cheng, Aochuan Chen, Nuo Chen +4
Low-Rank Adaptation (LoRA) has emerged as a prominent technique for fine-tuning large foundation models. Despite its successes, the substantial parameter redundancy, which limits t…
cs.LG2025
A Survey of Cross-domain Graph Learning: Progress and Future Directions
Haihong Zhao, Zhixun Li, Chenyi Zi +4
Graph learning plays a vital role in mining and analyzing complex relationships within graph data and has been widely applied to real-world scenarios such as social, citation, and…
cs.LG2024★ 5 cited
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen +4
Low-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank m…