6 citations · 17 across the 6 of their papers we have counts for
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cs.CV2023★ 3 cited
VIGC: Visual Instruction Generation and Correction
Bin Wang, Fan Wu, Xiao Han +8
The integration of visual encoders and large language models (LLMs) has driven recent progress in multimodal large language models (MLLMs). However, the scarcity of high-quality in…
cs.CV2023★ 5 cited
CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language Transformers
Dachuan Shi, Chaofan Tao, Anyi Rao +3
Recent vision-language models have achieved tremendous advances. However, their computational costs are also escalating dramatically, making model acceleration exceedingly critical…
cs.CV2023★ 6 cited
UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers
Dachuan Shi, Chaofan Tao, Ying Jin +3
Real-world data contains a vast amount of multimodal information, among which vision and language are the two most representative modalities. Moreover, increasingly heavier models,…