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When solving complex spatial reasoning tasks, ordinary humans naturally revisit the scenes from task-relevant viewpoints and mentally reconstruct the spatial layouts from those viewpoints. But can Large Vision-Language Models (LVLMs) proactively think in the same way? We term this ability Active Spatial Mentalization (...
This work introduces SciDocBench, a workflow-centered benchmark targeting capability diagnosis with verifiable training-data construction for scientific-document assistants, and SciDocIR, a structured representation of scientific document objects, layout and cross-reference relations, and provenance.
Scientific papers require models to reason jointly over text, equations, figures, tables, code, and datasets while preserving the provenance of supporting evidence. Existing benchmarks typically evaluate these capabilities in isolation, leaving unclear whether multimodal models can support realistic scientific-reading...
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