| # Subgroup Breakdown Report |
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| ## Scope |
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| - Source analysis run: `20260526_v2_official20_plus_c2patch_plus_subgroupconditionalrepair_merged49` |
| - Family analyzed: `subgroup_structure` |
| - Excluded models: `cdtd, codi, goggle` |
| - Included models: `12` |
| - Deduplicated dataset-model panels: `559` |
| - Subgroup query rows used: `12515` |
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| ## Canonical decomposition |
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| - `subgroup_structure = 0.5 * internal_profile_stability + 0.5 * subgroup_size_stability` |
| - `internal_profile_stability` captures subgroup-internal feature/distribution behavior. |
| - `subgroup_size_stability` captures whether subgroup support/size structure is preserved. |
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| ## Main findings |
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| 1. `REAL` is the expected perfect upper bound with subgroup score `1.000`. Among synthetic generators, `RealTabFormer` is strongest with mean subgroup score `0.790` across `49` datasets. |
| 2. `BayesNet` leans most toward internal-profile preservation (profile minus size = `0.002`), while `ForestDiffusion` is the clearest size-heavy model (profile minus size = `-0.033`). |
| 3. `TabDDPM` is the most balanced model between the two subgroup branches with mean absolute branch gap `0.000`. |
| 4. Dataset difficulty is uneven: `n9` is the hardest dataset on subgroup score (`0.091` mean across models), while `c3` is the easiest (`1.000`). |
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| ## Files to use first |
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| - `figures/subgroup_tradeoff_scatter_main.pdf` |
| - `figures/subgroup_branch_dumbbell_main.pdf` |
| - `figures/subgroup_prefix_bars_appendix.pdf` |
| - `tables/subgroup_model_summary_generated.tex` |
| - `data/model_summary.csv` |
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| ## Prefix note |
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| - Prefix coverage summary rows: `36` |
| - The `c / m / n` split is exported explicitly because subgroup behavior differs by dataset family, not just by overall model average. |
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