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Why 2D? (edit: just the vis or there is some other reason?)

Both the viz, and that the 2D UMAP projection is actually enough to get accurately delineated topics.

Hence why I think the typical embedding dimensionality is way way too high.

Do you think 1D could work? Maybe topic-space is some sort of tree-shaped structure where documents live in the thin strands.

1D could work on certain datasets but it wouldn't be ideal.

Why not just embed directly to 2d? Does it give worse results than UMAP?