Does Spatial Cognition Emerge in Frontier Models?
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913798919553024 |
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| author | Ramakrishnan, Santhosh Kumar Wijmans, Erik Kraehenbuehl, Philipp Koltun, Vladlen |
| author_facet | Ramakrishnan, Santhosh Kumar Wijmans, Erik Kraehenbuehl, Philipp Koltun, Vladlen |
| contents | Not yet. We present SPACE, a benchmark that systematically evaluates spatial cognition in frontier models. Our benchmark builds on decades of research in cognitive science. It evaluates large-scale mapping abilities that are brought to bear when an organism traverses physical environments, smaller-scale reasoning about object shapes and layouts, and cognitive infrastructure such as spatial attention and memory. For many tasks, we instantiate parallel presentations via text and images, allowing us to benchmark both large language models and large multimodal models. Results suggest that contemporary frontier models fall short of the spatial intelligence of animals, performing near chance level on a number of classic tests of animal cognition. Code and data are available: https://github.com/apple/ml-space-benchmark |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_06468 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Does Spatial Cognition Emerge in Frontier Models? Ramakrishnan, Santhosh Kumar Wijmans, Erik Kraehenbuehl, Philipp Koltun, Vladlen Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning Not yet. We present SPACE, a benchmark that systematically evaluates spatial cognition in frontier models. Our benchmark builds on decades of research in cognitive science. It evaluates large-scale mapping abilities that are brought to bear when an organism traverses physical environments, smaller-scale reasoning about object shapes and layouts, and cognitive infrastructure such as spatial attention and memory. For many tasks, we instantiate parallel presentations via text and images, allowing us to benchmark both large language models and large multimodal models. Results suggest that contemporary frontier models fall short of the spatial intelligence of animals, performing near chance level on a number of classic tests of animal cognition. Code and data are available: https://github.com/apple/ml-space-benchmark |
| title | Does Spatial Cognition Emerge in Frontier Models? |
| topic | Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2410.06468 |