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Models/SGCN

SGCN

Reported on 9 benchmarks across 3 tasks · 1 paper · 2 SOTA

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

Natural Language Processing5 results

Text ClassificationonOhsumed
Accuracy· 2019-02-19
68.5
best: 72.8 (RoBERTaGCN)
SOTA
Simplifying Graph Convolutional Networks arXiv:1902.07153
Sentiment AnalysisonMR
Accuracy· 2019-02-19
75.9
best: 93.3 (VLAWE)
Simplifying Graph Convolutional Networks arXiv:1902.07153
Text ClassificationonR52
Accuracy· 2019-02-19
94
best: 96.6 (1-6 BertGCN)
Simplifying Graph Convolutional Networks arXiv:1902.07153
Text ClassificationonR8
Accuracy· 2019-02-19
97.2
best: 98.451 (DeBERTa)
Simplifying Graph Convolutional Networks arXiv:1902.07153
Text Classificationon20NEWS
Accuracy· uses extra data· 2019-02-19
88.5
best: 93 (LinearSVM+TFIDF)
Simplifying Graph Convolutional Networks arXiv:1902.07153

Methodology4 results

ClassificationonOhsumed
Accuracy· 2019-02-19
68.5
best: 72.8 (RoBERTaGCN)
SOTA
Simplifying Graph Convolutional Networks arXiv:1902.07153
ClassificationonR52
Accuracy· 2019-02-19
94
best: 96.6 (1-6 BertGCN)
Simplifying Graph Convolutional Networks arXiv:1902.07153
ClassificationonR8
Accuracy· 2019-02-19
97.2
best: 98.451 (DeBERTa)
Simplifying Graph Convolutional Networks arXiv:1902.07153
Classificationon20NEWS
Accuracy· uses extra data· 2019-02-19
88.5
best: 93 (LinearSVM+TFIDF)
Simplifying Graph Convolutional Networks arXiv:1902.07153