110 citations · 128 across the 11 of their papers we have counts for
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cs.CV2024★ 4 cited
Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
Jihan Yang, Shusheng Yang, Anjali W. Gupta +3
Humans possess the visual-spatial intelligence to remember spaces from sequential visual observations. However, can Multimodal Large Language Models (MLLMs) trained on million-scal…
cs.CV2024★ 13 cited
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs
Shengbang Tong, Ellis Brown, Penghao Wu +11
We introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-centric approach. While stronger language models can enhance multimodal capabilities, the design…