Text Classification On R8

평가 지표

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	Accuracy	Paper Title	Repository
SGNN	98.09	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
C-BERT (ESGNN + BERT)	98.28	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
ESGNN	98.23	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
DistilBERT	97.981	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
SSGC	97.4	Simple Spectral Graph Convolution
fastText	96.13	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
SGC	97.2	Simplifying Graph Convolutional Networks	-
TM-Glove	97.50	Enhancing Interpretable Clauses Semantically using Pretrained Word Representation	-
GraphStar	97.4	Graph Star Net for Generalized Multi-Task Learning	-
WideMLP	96.98	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
ERNIE 2.0	98.041	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
DeBERTa	98.451	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
NABoE-full	97.1	Neural Attentive Bag-of-Entities Model for Text Classification	-
Our Model*	97.8	Text Level Graph Neural Network for Text Classification	-
Text GCN	97.07	Graph Convolutional Networks for Text Classification	-
SGCN	97.2	Simplifying Graph Convolutional Networks	-
BERT	98.171	Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets	-
TextEnt-full	96.7	Representation Learning of Entities and Documents from Knowledge Base Descriptions	-
RoBERTaGCN	98.2	BertGCN: Transductive Text Classification by Combining GCN and BERT	-
ConvTextTM	96.4	ConvTextTM: An Explainable Convolutional Tsetlin Machine Framework for Text Classification	-

0 of 21 row(s) selected.