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Document Classification On Reuters 21578
Document Classification On Reuters 21578
评估指标
F1
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
F1
Paper Title
Repository
MAGNET
89.9
MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network
-
VLAWE
89.3
Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation
KD-LSTMreg
88.9
DocBERT: BERT for Document Classification
LSTM-reg (single model)
87.0
Rethinking Complex Neural Network Architectures for Document Classification
-
SCDV-MS
82.71
Improving Document Classification with Multi-Sense Embeddings
ApproxRepSet
-
Rep the Set: Neural Networks for Learning Set Representations
REL-RWMD k-NN
-
Speeding up Word Mover's Distance and its variants via properties of distances between embeddings
Orthogonalized Soft VSM
-
Text classification with word embedding regularization and soft similarity measure
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Document Classification On Reuters 21578 | SOTA | HyperAI超神经