HyperAI超神経

Text Classification On Trec 6

評価指標

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評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
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Paper TitleRepository
VLAWE5.8Vector of Locally-Aggregated Word Embeddings (VLAWE): A Novel Document-level Representation
DELTA (CNN)7.8DELTA: A DEep learning based Language Technology plAtform
CoVe4.2Learned in Translation: Contextualized Word Vectors
MPAD-path6.2Message Passing Attention Networks for Document Understanding-
SWEM-aver7.8Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
Capsule-B7.2Investigating Capsule Networks with Dynamic Routing for Text Classification
CNN+MCFA4Translations as Additional Contexts for Sentence Classification
BERT-ITPT-FiT3.2How to Fine-Tune BERT for Text Classification?
RoBERTa+DualCL2.60Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation
GRU-RNN-GLOVE7.0All-but-the-Top: Simple and Effective Postprocessing for Word Representations
ULMFiT3.6Universal Language Model Fine-tuning for Text Classification
LSTM-CNN3.9Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling
Automatic Label Error Correction0.40The Re-Label Method For Data-Centric Machine Learning-
TBCNN4Discriminative Neural Sentence Modeling by Tree-Based Convolution-
USE_T+CNN1.93Universal Sentence Encoder
TM-Glove9.96Enhancing Interpretable Clauses Semantically using Pretrained Word Representation
C-LSTM5.4A C-LSTM Neural Network for Text Classification
byte mLSTM79.6A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
STM+TSED+PT+2L7.04The Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble Learning
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