There are 27 repositories under abstractive-text-summarization topic.
A curated list of resources dedicated to text summarization
Multiple implementations for abstractive text summurization , using google colab
Abstractive summarisation using Bert as encoder and Transformer Decoder
This repository contains the code, data, and models of the paper titled "XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages" published in Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021.
Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.
Abstractive Text Summarization using Transformer
ACL 2020 Unsupervised Opinion Summarization as Copycat-Review Generation
A tool to automatically summarize documents abstractively using the BART or PreSumm Machine Learning Model.
Gazeta: Dataset for automatic summarization of Russian news / Газета: набор данных для автоматического реферирования на русском языке
[AAAI2021] Unsupervised Opinion Summarization with Content Planning
[ACL-IJCNLP 2021] Self-Supervised Multimodal Opinion Summarization
[ACL2020] Unsupervised Opinion Summarization with Noising and Denoising
An optimized Transformer based abstractive summarization model with Tensorflow
Pytorch implementation of Get To The Point: Summarization with Pointer-Generator Networks (2017) by Abigail See et al.
non-anonymized cnn/dailymail dataset for text summarization
Generates summary of a given news article. Used attention seq2seq encoder decoder model.
Speaker Diarization + Speech to text + abstract summerization
Abstractiv Text Summarization
Abstractive Summarization in the Nepali language
Abstractive Text Summarization using Transformer model
tensorflow2 implementation of se2seq with attention for context generation
Abstractive text summarisation using BART model on articles data.
Text summarization with human feed-back
Corner stone seq2seq with attention (using bidirectional ltsm )
An ai-as-a-service for abstractive text summarizaion
SumSimple is a FastAPI-based text summarization service using traditional, non-LLM algorithms like SumBasic, Luhn, Edmundson, LexRank, TextRank, and LSA.
An AI tool to gain insight into X (Twitter) trends through web-scraping, natural language processing, and abstractive summarization.
[Computer Speech & Language, Elsevier] - Neural Sentence Fusion for Diversity Driven Abstractive Multi-Document Summarization.
Abstractive Text Summarization of Amazon reviews. Using LSTM model summary of full review is abstracted
Prepare Text Reviews Summary
Abstractive text summarization generates a shorter version of a given sentence while attempting to preserve its contextual meaning. In our approach we model the problem using an attentional encoder decoder which ensures that the decoder focuses on the appropriate input words at each step of our generation.
Welcome to our Summarizer App! This tool is designed to help you efficiently condense lengthy articles and text into concise summaries, making it easier for you to grasp the main points without spending too much time reading.
perfroming abstractive text summariztion task using T5, and serving it via REST API
YouTube Transcript Summarization over Flask: This back-end uses Flask framework to receive API calls from the client and then respond with the summarized text response. This API can work only on those YouTube videos which has well-formatted closed captions in it. The same backend also hosts a web version of the Summarizer.