From Human Cognition to Neural Activations: Probing the Computational Primitives of Spatial Reasoning in LLMs
As spatial intelligence becomes an increasingly important capability for foundation models, it remains unclear whether large language models' (LLMs) performance on spatial reasoning benchmarks reflects structured internal spatial representations or reliance on linguistic heuristics. We address this question from a mechanistic perspective by examining how spatial information is internally represented and used. Drawing on computational theories of human spatial cognition, we decompose spatial reasoning into three primitives, relational composition, representational transformation, and stateful spatial updating, and design controlled task families for each. We evaluate multilingual LLMs in E...
| Authors | Jiyuan An, Liner Yang, Mengyan Wang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 27 March 2026 |
| Last updated at source | 27 March 2026 |
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