Text Summarizer is an NLP-driven application designed to provide concise summaries of large text documents. Leveraging advanced algorithms and machine learning techniques, this project streamlines the process of information retrieval, making it easier for users to grasp key points quickly.
Reproducing ACL Paper for iterative text generation and performing Robustness and Multilinguality tests
This repository explores enhancing dialogue summarization with commonsense knowledge through the SICK framework, evaluating models on dialogue datasets to assess commonsense's impact on summarization quality.
This project 'Rare Word - Text summarization' use Language Model for the text summarization and also used Kaggle dataset by Web Scrapping
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