TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/G-Tuning

G-Tuning

Reported on 30 benchmarks across 2 tasks · 1 paper · 20 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Graphs15 results

  • Graph ClassificationonIMDb-B
    Accuracy (10-fold)· 2023-12-21
    74.3
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonREDDIT-12K
    Accuracy (10 fold)· 2023-12-21
    42.8
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonMSRC-21 (per-class)
    Accuracy (10 fold)· 2023-12-21
    11.01
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonIMDb-M
    Accuracy (10-fold)· 2023-12-21
    51.8
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonBACE
    ROC-AUC· 2023-12-21
    84.79
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph Classificationonclintox
    ROC-AUC· 2023-12-21
    74.64
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonBBBP
    ROC-AUC· 2023-12-21
    72.59
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonMUTAG
    Accuracy (10 fold)· 2023-12-21
    86.14
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonPROTEINS
    Accuracy (10 fold)· 2023-12-21
    72.05
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonENZYMES
    Accuracy (10-fold)· 2023-12-21
    26.7
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonSIDER
    ROC-AUC· 2023-12-21
    61.4
    best: 63.5 (GTOT-Tuning)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonMUV
    ROC-AUC· 2023-12-21
    75.84
    best: 80 (GTOT-Tuning)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonToxCast
    ROC-AUC· 2023-12-21
    64.25
    best: 65.44 (GMT)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonHIV
    ROC-AUC· 2023-12-21
    77.33
    best: 78.2 (GTOT-Tuning)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Graph ClassificationonTox21
    ROC-AUC· 2023-12-21
    75.8
    best: 77.3 (GMT)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583

Methodology15 results

  • ClassificationonIMDb-B
    Accuracy (10-fold)· 2023-12-21
    74.3
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonREDDIT-12K
    Accuracy (10 fold)· 2023-12-21
    42.8
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonMSRC-21 (per-class)
    Accuracy (10 fold)· 2023-12-21
    11.01
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonIMDb-M
    Accuracy (10-fold)· 2023-12-21
    51.8
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonBACE
    ROC-AUC· 2023-12-21
    84.79
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • Classificationonclintox
    ROC-AUC· 2023-12-21
    74.64
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonBBBP
    ROC-AUC· 2023-12-21
    72.59
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonMUTAG
    Accuracy (10 fold)· 2023-12-21
    86.14
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonPROTEINS
    Accuracy (10 fold)· 2023-12-21
    72.05
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonENZYMES
    Accuracy (10-fold)· 2023-12-21
    26.7
    SOTA
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonSIDER
    ROC-AUC· 2023-12-21
    61.4
    best: 63.5 (GTOT-Tuning)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonMUV
    ROC-AUC· 2023-12-21
    75.84
    best: 80 (GTOT-Tuning)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonToxCast
    ROC-AUC· 2023-12-21
    64.25
    best: 65.44 (GMT)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonHIV
    ROC-AUC· 2023-12-21
    77.33
    best: 78.2 (GTOT-Tuning)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583
  • ClassificationonTox21
    ROC-AUC· 2023-12-21
    75.8
    best: 77.3 (GMT)
    Fine-tuning Graph Neural Networks by Preserving Graph Generative PatternsarXiv:2312.13583