Advancing Fake News Detection: Hybrid Deep Learning With FastText and Explainable AI

5,500.00
To develop a robust and explainable hybrid deep learning framework for detecting fake news by integrating advanced transformer-based models and explainable AI techniques, thereby enhancing classification accuracy, improving model generalization, and fostering transparency in decision-making

AI-Generated vs. Human Text: Introducing a New Dataset for Benchmarking and Analysis

5,500.00

Aim: The aim of this project is to enhance the ability to distinguish between AI-generated and human-authored text by utilizing a fine-tuned BERT classifier. This approach emphasizes contextual understanding and deep language representation to outperform traditional machine learning systems in identifying AI-generated content.