most citedSVFit: Parameter-Efficient Fine-Tuning of Large Pre-Trained Models Using Singular Values

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cs.LG2026

Quantum-Inspired Fine-Tuning for Few-Shot AIGC Detection via Phase-Structured Reparameterization

Kaiyang Xing, Han Fang, Zhaoyun Chen +4

Recent studies show that quantum neural networks (QNNs) generalize well in few-shot regimes. To extend this advantage to large-scale tasks, we propose Q-LoRA, a quantum-enhanced fi…

cs.LG2024★ 2 cited

SVFit: Parameter-Efficient Fine-Tuning of Large Pre-Trained Models Using Singular Values

Chengwei Sun, Jiwei Wei, Yujia Wu +5

Large pre-trained models (LPMs) have demonstrated exceptional performance in diverse natural language processing and computer vision tasks. However, fully fine-tuning these models…