Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Human researchers outperformed large language models across all major stages of systematic review preparation, particularly in study selection, synthesis, and final manuscript drafting. While LLMs ...

Abstract: Text summarization, which is the process of making a brief summary of text while preserving its overall meaning, is an important problem in Natural Language Processing (NLP). Automatic ...

Introduction: Plant phenotyping is a critical area in agricultural research that focuses on assessing plant traits quantitatively to enhance productivity and sustainability. While traditional methods ...

Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...

Students call it hypocritical. A senior at Northeastern University demanded her tuition back. But instructors say generative A.I. tools make them better at their jobs. By Kashmir Hill In February, ...

Abstract: This project focused on using clinical text data from the PubMed dataset to train transformer models and deep learning models for text summarization. The primary goal was to develop a system ...