Neural abstractive summarization (seq2seq + copy (or pointer network) + coverage) in pytorch on CNN/Daily Mail

non-anonymized cnn/dailymail dataset for text summarization

Abstractive text summarization using CNN/DailyMail Dataset training on RNN/LSTM & T5.

A script to process non-anonymized CNN and DailyMail for summary.

Code to obtain raw texts of the CNN / Daily Mail dataset (non-anonymized) for summarization (python3)

AACL'2022: Unsupervised Single Document Abstractive Summarization using Semantic Units

NLP CNN Daily Mail News Abstractive Text Summarisation

Gated Attention Reader for Cloze style question answering and reading comphrehension, implemented in PyTorch

Pointer-Generator Networks with Different Word Embeddings for Abstractive Summarization

A transformer-based models to enhance text summarization with a focus on rare and infrequently used words built with CNN/DailyMail Dataset using PyTorch, NLTK, Bidirectional Auto-Regressive Transformers(BART)

This repository contains an implementation of a text summarization model using the T5 (Text-To-Text Transfer Transformer) architecture. The goal of this project is to build a system that can generate concise summaries from lengthy news articles, specifically using the CNN/DailyMail dataset.