Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?

• URL: http://arxiv.org/abs/2602.07055v1
• Date: Wed, 04 Feb 2026 19:06:40 GMT
• Title: Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?
• Abstract summary: Theory of Space is defined as an agent's ability to actively acquire information through self-directed, active exploration.<n>A key innovation is spatial belief probing, which prompts models to reveal their internal spatial representations at each step.<n>Our findings suggest that current foundation models struggle to maintain coherent, revisable spatial beliefs during active exploration.
• Score: 83.13508919229939
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Spatial embodied intelligence requires agents to act to acquire information under partial observability. While multimodal foundation models excel at passive perception, their capacity for active, self-directed exploration remains understudied. We propose Theory of Space, defined as an agent's ability to actively acquire information through self-directed, active exploration and to construct, revise, and exploit a spatial belief from sequential, partial observations. We evaluate this through a benchmark where the goal is curiosity-driven exploration to build an accurate cognitive map. A key innovation is spatial belief probing, which prompts models to reveal their internal spatial representations at each step. Our evaluation of state-of-the-art models reveals several critical bottlenecks. First, we identify an Active-Passive Gap, where performance drops significantly when agents must autonomously gather information. Second, we find high inefficiency, as models explore unsystematically compared to program-based proxies. Through belief probing, we diagnose that while perception is an initial bottleneck, global beliefs suffer from instability that causes spatial knowledge to degrade over time. Finally, using a false belief paradigm, we uncover Belief Inertia, where agents fail to update obsolete priors with new evidence. This issue is present in text-based agents but is particularly severe in vision-based models. Our findings suggest that current foundation models struggle to maintain coherent, revisable spatial beliefs during active exploration.

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