2 papers
cs.CV2025
ZOO-Prune: Training-Free Token Pruning via Zeroth-Order Gradient Estimation in Vision-Language Models
Youngeun Kim, Youjia Zhang, Huiling Liu +3
Large Vision-Language Models (VLMs) enable strong multimodal reasoning but incur heavy inference costs from redundant visual tokens. Token pruning alleviates this issue, yet existi…
cs.LG2025
Dynamic Rank Adjustment for Accurate and Efficient Neural Network Training
Hyuntak Shin, Aecheon Jung, Sungeun Hong +1
Low-rank training methods reduce the number of trainable parameters by re-parameterizing the weights with matrix decompositions (e.g., singular value decomposition). However, enfor…