You'll test a Log-linear classifier with TFIDF, fine-tune a Transformer model, and apply zero-shot classification. Assess accuracy, dataset sensitivity, and model pros and cons.

A new study presents a hybrid Transformer-LSTM model that improves the detection of AI-generated text by analyzing semantic similarity for enhanced content verification.

This project aims to deepen the understanding of Transformer architectures by implementing and experimenting with different components, improving model performance, and gaining insights into the ...

We propose a new gating mechanism to dynamically adjust the information flow, which improving the sensitivity of the Transformer model to key features. Finally, the feature is fed into a linear ...

Consequently, this paper presents a novel linear-complexity data-efficient image ... convolutional neural network to provide knowledge to the transformer-based student model for the classification of ...