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cs.CV2026
Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs
Jaeyeon Lee, Shunjie Wen, Dong-Wan Choi
Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual tokens. While diversity maximization…
cs.CV2025
Lossless Token Merging Even Without Fine-Tuning in Vision Transformers
Jaeyeon Lee, Dong-Wan Choi
Although Vision Transformers (ViTs) have become the standard architecture in computer vision, their massive sizes lead to significant computational overhead. Token compression tech…