297 citations · 439 across the 18 of their papers we have counts for
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cs.CV2023
How (not) to ensemble LVLMs for VQA
Lisa Alazraki, Lluis Castrejon, Mostafa Dehghani +3
This paper studies ensembling in the era of Large Vision-Language Models (LVLMs). Ensembling is a classical method to combine different models to get increased performance. In the…
cs.CV2023★ 118 cited
Scaling Vision Transformers to 22 Billion Parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa +39
The scaling of Transformers has driven breakthrough capabilities for language models. At present, the largest large language models (LLMs) contain upwards of 100B parameters. Visio…