Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
Memory-Efficient Fine-Tuning via Low-Rank Activation Compression
Jiang-Xin Shi, Wen-Da Wei, Jin-Fei Qi +3
The parameter-efficient fine-tuning paradigm has garnered significant attention with the advancement of foundation models. Although numerous methods have been proposed to reduce th…
cs.LG2025
Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning
Lin-Han Jia, Si-Yu Han, Wen-Chao Hu +5
The effectiveness of unlabeled data in Semi/Self-Supervised Learning (SSL) depends on appropriate assumptions for specific scenarios, thereby enabling the selection of beneficial u…