Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
Jihan Yang; Shusheng Yang; Anjali Gupta; Rilyn Han; Li Fei-Fei; Saining Xie · 2025
WASTE classifies this as Failed Experiment Report · AI classification, approximate
An experimental approach did not work as intended — learn what to avoid before investing the same effort.
Abstract (excerpt)
Humans possess the visual-spatial intelligence to remember spaces from sequential visual observations. However, can Multimodal Large Language Models (MLLMs) trained on million-scale video datasets also "think in space" from videos? We…
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Metadata source: OpenAlex · DOI 10.1109/cvpr52734.2025.00994