chart and document understanding

This is the skill of reading structured visual information — a bar chart, a spreadsheet table, an invoice, a multi-page PDF, a scientific figure — and answering questions or pulling out data. Which quarter had the highest revenue? Extract every line item and its price. It is where multimodal LLMs become genuinely useful at work, turning a screenshot of a report into something you can query in plain language.

It combines several abilities at once: OCR to read the numbers and labels, layout understanding to know which cell or axis a value belongs to, and reasoning to compare, sum, or spot a trend. Models are trained on large collections of charts and documents paired with question-answer data, sometimes with the underlying tables provided so the model learns to recover structure, not just pixels. High resolution matters more here than for natural photos, because the information is the small text.

Arithmetic over what it reads is a weak point — a model may parse a table correctly yet miscompute the total — so pairing it with a calculator or code tool, rather than trusting its mental maths, is the reliable pattern.