SOURCE-LINKED INTELLIGENCE
SciDocBench: A Workflow-Centered Benchmark and Data Pipeline for Scientific Document Understanding
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 workflows. We introduce SciDocBench, a workflow-centered benchmark for scientific document understanding. It contains 124 expert-authored and difficulty-screened questions organized into seven research-assistant capability groups and 19 subtasks across five scientific domains. Ea
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-04T13:39:48.000Z
First collected: 2026-09-20T21:52:07.471Z. This is not the publication date.