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CNN-Trans-Enc: A CNN-Enhanced Transformer-Encoder On Top Of Static BERT representations for Document Classification
CNN-Trans-Enc is relatively small as a downstream classifier and doesn't require any fine-tuning of BERT, as it ensures an optimal use of the $[CLS]$ representations from all layers, leveraging different linguistic features with more meaningful, and generalizable QKV representations of the input.
Hybrid Multisource Feature Fusion for the Text Clustering
The text clustering technique is an unsupervised text mining method which are used to partition a huge amount of text documents into groups.
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