{
  "metadata": {
    "title": "SUPREME published results: Pins Face Recognition",
    "paper_url": "https://arxiv.org/abs/2606.00380",
    "paper_title": "SUPREME: A Multi-GPU Framework for Reproducible Image Unlearning Method Evaluation",
    "reference_release": "v0.1.0-paper",
    "dataset": "Pins Face Recognition",
    "models": [
      "ResNet18",
      "ViT"
    ],
    "training_seeds": [
      260,
      261,
      262,
      263,
      264,
      265,
      266,
      267,
      268,
      269
    ],
    "seed_protocol": "Matched: J = K = 1; training, unlearning and evaluation seeds coincide within a run.",
    "hardware": "One NVIDIA L40S GPU (48 GB)",
    "fullclass_targets": [
      "alex_lawther",
      "bill_gates",
      "danielle_panabaker",
      "hugh_jackman",
      "josh_radnor"
    ],
    "random_forget_fraction": 0.001,
    "aggregation": "Full-class: average over five forget classes within each seed, then mean and standard deviation over ten seeds. Random: mean and standard deviation over ten seeds for a 0.1% forget set.",
    "data_kind": "Published aggregate values, transcribed at the paper's two-decimal precision. These files contain no individual-seed measurements or model checkpoints.",
    "accuracy_unit": "percent for raw accuracy; percentage points for differences",
    "difference_definition": "Unlearned minus retrained. Closer to zero indicates closer agreement on that metric, not proof of data removal.",
    "error_bars": "One standard deviation across seeds, not confidence intervals. Symmetric bars may extend beyond a metric's physical range.",
    "rounding": "Differences were copied from the reported difference tables, not recalculated from rounded raw means. Values displayed as -0.00 retain the source sign in CSV.",
    "excluded": "UNSIR is excluded from the random-sample scenario by design. Original-model values and execution times are not supplied by these three paper tables.",
    "tables": {
      "pins_main.csv": "Table 1: Accuracy differences and layer-wise distances (LaTeX label tab:pins_results_main).",
      "pins_additional.csv": "Appendix: MIA differences and activation distances (LaTeX label tab:pins_results_appendix).",
      "pins_raw.csv": "Appendix: Raw accuracy and MIA summaries, including the retrained reference (LaTeX label tab:pins_raw_values)."
    }
  },
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      "scenario": "fullclass",
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      "forget_accuracy_difference_std": "5.21",
      "retain_accuracy_difference_mean": "2.52",
      "retain_accuracy_difference_std": "0.11",
      "layer_distance_mean": "31.52",
      "layer_distance_std": "0.22"
    },
    {
      "model": "ResNet18",
      "scenario": "fullclass",
      "method": "BadT",
      "forget_accuracy_difference_mean": "0.26",
      "forget_accuracy_difference_std": "0.17",
      "retain_accuracy_difference_mean": "-2.35",
      "retain_accuracy_difference_std": "0.27",
      "layer_distance_mean": "31.72",
      "layer_distance_std": "0.34"
    },
    {
      "model": "ResNet18",
      "scenario": "fullclass",
      "method": "UNSIR",
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      "forget_accuracy_difference_std": "1.98",
      "retain_accuracy_difference_mean": "2.51",
      "retain_accuracy_difference_std": "0.12",
      "layer_distance_mean": "32.25",
      "layer_distance_std": "0.34"
    },
    {
      "model": "ResNet18",
      "scenario": "fullclass",
      "method": "RL",
      "forget_accuracy_difference_mean": "0.00",
      "forget_accuracy_difference_std": "0.00",
      "retain_accuracy_difference_mean": "2.58",
      "retain_accuracy_difference_std": "0.12",
      "layer_distance_mean": "31.98",
      "layer_distance_std": "0.34"
    },
    {
      "model": "ResNet18",
      "scenario": "fullclass",
      "method": "SSD",
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      "forget_accuracy_difference_std": "6.22",
      "retain_accuracy_difference_mean": "-9.14",
      "retain_accuracy_difference_std": "7.43",
      "layer_distance_mean": "31.55",
      "layer_distance_std": "0.36"
    },
    {
      "model": "ResNet18",
      "scenario": "fullclass",
      "method": "LFSSD",
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      "forget_accuracy_difference_std": "0.00",
      "retain_accuracy_difference_mean": "-3.66",
      "retain_accuracy_difference_std": "1.53",
      "layer_distance_mean": "31.56",
      "layer_distance_std": "0.34"
    },
    {
      "model": "ResNet18",
      "scenario": "random",
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      "forget_accuracy_difference_std": "24.32",
      "retain_accuracy_difference_mean": "-2.60",
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