Introduction and Demo This project focuses on abstractive text summarization using deep learning models. The goal is to generate concise summaries that retain the core content of the original text.

What’s happened? Perplexity AI just dropped a new language learning feature built right into its platform. In a post shared on social media, the company announced a tool that helps users learn by ...

While China’s AI sector continues to accelerate, driving economic growth and reshaping entire industries, a growing number of researchers are turning their focus toward using AI for social good. Among ...

AI Text Summarization App - A React-based web app that uses three different AI models (BART, Pegasus, T5) to generate high-quality text summaries with sentiment analysis, export options, and a modern ...

Abstract: Document summarization aims to create a precise and coherent summary of a text document. Many deep learning summarization models are developed mainly for English, often requiring a large ...

A feature summarization approach, leveraging TF-IDF and K-means clustering, was employed to extract and distill key radiological findings related to three diseases. Simultaneously, the hybrid RAG ...

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, ...

Objective: This study aims to present the current state of the art on clinical text summarization using large language models, evaluate the level of evidence in existing research and assess the ...