Can I add a third dimension?

Encode it as dot size or color (e.g., dot diameter ∝ accuracy, color ∝ year of publication).

ComparisonText → ImageLow creditEN

Four-Quadrant Positioning Matrix

Two-axis scatter dividing options into four labeled quadrants with example methods placed inside.

When to use this prompt

For positioning related work, market segmentation, or method-classification tables.

The prompt

A 2x2 positioning matrix with two axes and four labeled quadrants.

Axes:
- X-axis (horizontal): "Data Efficiency" — left = low, right = high
- Y-axis (vertical): "Compute Efficiency" — bottom = low, top = high

Four quadrants:
- Top-left: "Compute-Hungry, Data-Rich" — methods that need lots of compute and tolerate data scarcity (e.g., huge pretraining)
- Top-right: "Sweet Spot" — high efficiency on both axes (e.g., distilled small models)
- Bottom-left: "Avoid" — both inefficient (e.g., naive scratch training)
- Bottom-right: "Data-Greedy, Cheap" — needs lots of data but cheap to run (e.g., kNN retrieval)

Plot 6-8 example methods as labeled dots distributed across all four quadrants. Each dot has a 1-2 word label.

Style: clean publication-style scatter, white background, slate axes with one accent color per quadrant, sans-serif. Quadrant headers in upper-corner of each quadrant. Suitable for survey papers and consultancy decks.

Variations

With evolutionary arrow

Add a curved arrow showing how the field has moved over time, e.g. starting bottom-left in 2018 and ending top-right by 2025, passing through several method dots.

Tips

Label both axes with units / endpoints (low / high). Unlabeled axes confuse readers.
Place quadrant headers in corners, not centers — they otherwise compete with the data dots.
Cap dots at 8. More than that obscures the positioning narrative.