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cs.CV2026
What Do Visual Tokens Really Encode? Uncovering Sparsity and Redundancy in Multimodal Large Language Models
Yingqi Fan, Junlong Tong, Anhao Zhao +1
Multimodal large language models (MLLMs) project visual tokens into the embedding space of language models, yet the internal structuring and processing of visual semantics remain p…
cs.CV2026
ViCA: Efficient Multimodal LLMs with Vision-Only Cross-Attention
Wenjie Liu, Hao Wu, Xin Qiu +6
Modern multimodal large language models (MLLMs) adopt a unified self-attention design that processes visual and textual tokens at every Transformer layer, incurring substantial com…
cs.CV2025
: Decoding Discontinuous Cross-Modal Dynamics for Efficient Multimodal LLMs
Yingqi Fan, Anhao Zhao, Jinlan Fu +5
Multimodal Large Language Models (MLLMs) have achieved strong performance across vision-language tasks, but suffer from significant computational overhead due to the quadratic grow…