Interactive lab

The graph explorer

How to read the graph

Fix one evaluation slice first. Then read each node as a possible training set and each edge as a one-step move in dataset space. Moving downward removes data, moving upward adds data, and longer paths let you trace a strike or coordinated ablation instead of only reading a single local comparison.

The graph explorer works best on a wider screen because the middle layers of the subset lattice can get wide.

Graph explorer

Walk the subset lattice directly.

Instead of scanning the full train-by-eval matrix, fix an evaluation slice and move through the graph of possible training sets. Nodes are training worlds; one-step edges become ablations, augmentations, or steps inside a larger strike path.

Universe size
4 datasets
The graph has 16 nodes once every possible subset is enumerated.
Score rule
Normalized overlap: a rough performance proxy when train and eval look similar, but still only set similarity.
Graph lens
Highlight one single-step deletion from the selected training node.
Clicking a node in the lattice updates this too.
Focus contributor
Choose the dataset whose edge additions or deletions you want to inspect.
Subset lattice

Nodes are training sets; colors read off the active eval slice.

Ablation edgeTrain ABCDEval ABCDJaccard
Selected train nodeCurrent walkUnselected edit edge
B∅ABCDABACADBCBDCDABCABDACDBCDABCD
Midpoint nodes can get wide as the universe grows. The canvas scrolls horizontally so the full lattice stays inspectable.
Current lens

Follow one ablation edge

Ablation delta: 0.2500

Move from train ABCD to ACD while keeping eval ABCD fixed.

Selected score1.0000
Train nodeABCD
Eval sliceABCD
Node degree4
f(ABCD, ABCD) - f(ACD, ABCD) = 0.2500
One-step edits

Neighbors of ABCD

Eval ABCD
Single deletions
Single additions
  • The full training set has no outgoing augmentation edges.