In this paper, we analyze the difference between BERT-style and CLIP-style text encoders from three experiments: (i) general text understanding, (ii) vision-centric text understanding, and (iii) text-to-image generation. Experimental analyses show that although CLIP-style text encoders ...
We use the BERT for text representation, the output vectors of BERT are dimension reduced through the sparse autoencoder, and then the Softmax classifier takes the reduced vectors as input to get the prediction of the input text. Experimental results show that our method mitigate the unbalance ...
BERT (Google):Bidirectional Encoder Representations from Transformers (BERT) was developed by Google. Unlike GPT models that predict the next word in a sequence, BERT is designed for tasks requiring understanding the entire sentence context. It's pre-trained on a huge amount of text to learn con...
X-BERT: eXtreme Multi-label Text Classification with using Bidirectional Encoder Representations from TransformersWei-Cheng ChangHsiang-Fu YuKai ZhongYiming YangInderjit Dhillon