Track: research · Level: core · Effort: ~8h · Depends on: #335 (T20)
Why this matters
Accuracy alone does not prove BNNR fixes the right problem. The XAI metrics and overlays show, visually and quantitatively, that ICD makes the model rely less on background shortcuts. This is the evidence that turns 'our numbers went up' into 'and here is why', which is what convinces a technical audience and a paper reviewer.
Steps
- From the per-run XAI metrics already produced by the benchmark (edge_ratio, coverage, gini), build a cross-condition table.
- Compute the correlation (Spearman) between edge_ratio and accuracy across runs.
- Assemble the OptiCAM overlay figure on the fixed validation indices, showing the model before and after ICD.
- Write the interpretation in findings.md: what the metrics say about shortcut reliance.
Done when
An XAI metrics table, a correlation result, and the overlay figure, all regenerable from the committed runs.
How to take this: comment "taking this" and wait to be assigned. Branch t22-short-desc from upstream/main, and put Closes #<this issue number> in your PR. Full workflow: the Cohort Handbook (pinned in Discord).
Track: research · Level: core · Effort: ~8h · Depends on: #335 (T20)
Why this matters
Accuracy alone does not prove BNNR fixes the right problem. The XAI metrics and overlays show, visually and quantitatively, that ICD makes the model rely less on background shortcuts. This is the evidence that turns 'our numbers went up' into 'and here is why', which is what convinces a technical audience and a paper reviewer.
Steps
Done when
An XAI metrics table, a correlation result, and the overlay figure, all regenerable from the committed runs.
How to take this: comment "taking this" and wait to be assigned. Branch
t22-short-descfromupstream/main, and putCloses #<this issue number>in your PR. Full workflow: the Cohort Handbook (pinned in Discord).