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cs.LG2025
ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs
Weigang Lu, Ziyu Guan, Wei Zhao +5
GNN-to-MLP (G2M) methods have emerged as a promising approach to accelerate Graph Neural Networks (GNNs) by distilling their knowledge into simpler Multi-Layer Perceptrons (MLPs).…
cs.SE2025
Leveraging Metamemory Agent for Enhanced Data-Free Code Generation in Large Language Models
Shengsheng Zhou, Shuai Wang, Liang Ding +5
Large language models (LLMs) have shown strong performance in automated code generation, with few-shot prompting widely used for its simplicity and effectiveness. However, few-shot…