7 citations · 18 across the 18 of their papers we have counts for
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cs.CV2024★ 2 cited
Token-level Correlation-guided Compression for Efficient Multimodal Document Understanding
Renshan Zhang, Yibo Lyu, Rui Shao +3
Cropping high-resolution document images into multiple sub-images is the most widely used approach for current Multimodal Large Language Models (MLLMs) to do document understanding…
cs.CV2024★ 4 cited
MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models
Leyang Shen, Gongwei Chen, Rui Shao +2
Multimodal large language models (MLLMs) have demonstrated impressive capabilities across various vision-language tasks. However, a generalist MLLM typically underperforms compared…