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cs.LG2026
Understanding and Guiding Layer Placement in Parameter-Efficient Fine-Tuning of Large Language Models
Yichen Xu, Yuyang Liang, Shan Dai +3
As large language models (LLMs) continue to grow, the cost of full-parameter fine-tuning has made parameter-efficient fine-tuning (PEFT) the default strategy for downstream adaptat…
cs.LG2025
Rethinking Semi-Supervised Node Classification with Self-Supervised Graph Clustering
Songbo Wang, Renchi Yang, Yurui Lai +2
The emergence of graph neural networks (GNNs) has offered a powerful tool for semi-supervised node classification tasks. Subsequent studies have achieved further improvements throu…