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Text Classification On Ag News

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Résultats

Résultats de performance de divers modèles sur ce benchmark

Paper Title
ToWE-SG14.0Task-oriented Word Embedding for Text Classification
Seq2CNN with GWS(50)9.64Abstractive Text Classification Using Sequence-to-convolution Neural Networks
Char-level CNN9.51Character-level Convolutional Networks for Text Classification
SVDCNN9.45Squeezed Very Deep Convolutional Neural Networks for Text Classification
VDCN8.67Very Deep Convolutional Networks for Text Classification
Balanced+bi-leaf-RNN7.9On Tree-Based Neural Sentence Modeling
CCCapsNet7.61Compositional Coding Capsule Network with K-Means Routing for Text Classification
LEAM7.55Joint Embedding of Words and Labels for Text Classification
fastText7.5Bag of Tricks for Efficient Text Classification
Capsule-B 7.4Investigating Capsule Networks with Dynamic Routing for Text Classification
SWEM-concat7.34Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
EXAM7Explicit Interaction Model towards Text Classification
DPCNN6.87Deep Pyramid Convolutional Neural Networks for Text Categorization
CNN6.57Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings
ULMFiT (Small data)6.3Sampling Bias in Deep Active Classification: An Empirical Study
DNC+CUW6.10Learning to Remember More with Less Memorization
DRNN5.53Disconnected Recurrent Neural Networks for Text Categorization
ULMFiT5.01Universal Language Model Fine-tuning for Text Classification
L MIXED4.95Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function
BERT-ITPT-FiT4.8How to Fine-Tune BERT for Text Classification?
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Text Classification On Ag News | SOTA | HyperAI