Popular GitHub Repositories for Abstractive Summarization

Code for ACL 2018 paper: "Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting. Chen and Bansal"

Abstractive summarisation using Bert as encoder and Transformer Decoder

A Abstractive Summarization Implementation with Transformer and Pointer-generator

Pointer-generator reinforced seq2seq summarization in PyTorch

Source code for the NAACL 2019 paper "SEQ^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression"

FactSumm: Factual Consistency Scorer for Abstractive Summarization

A tool to automatically summarize documents abstractively using the BART or PreSumm Machine Learning Model.

Codebase for the Summary Loop paper at ACL2020

Abstractive text summarization by fine-tuning seq2seq models.

The code repository for NAACL 2021 paper "AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization".

[ACL-IJCNLP 2021] Self-Supervised Multimodal Opinion Summarization

The source code for my bachelor's thesis "Abstractive Summarization of Meetings"

Code for paper "Extract, Denoise and Enforce: Evaluating and Improving Concept Preservation for Text-to-Text Generation" EMNLP 2021 and "Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation" arXiv 2020

A system capable of converting Nepali speech to text and generate summary of text

An optimized Transformer based abstractive summarization model with Tensorflow

Text Summarization on Spotify Podcast Transcripts for NLP class at @UNIBO

This repository contains code and resources for abstractive text summarization (TS) using a novel framework that leverages knowledge-based word sense disambiguation (WSD) and semantic content generalization to enhance the performance of sequence-to-sequence (seq2seq) neural-based TS.

Code and data for the Dreyer et al (2023) paper on abstractiveness and factuality in abstractive summarization

An experimental custom seq-2-seq model with both layer-wise (inter-layer), and intra-layer attention (attention to previous hidden states of the same RNN unit) for abstractive summarization.

Longformer Encoder Decoder model for the legal domain, trained for long document abstractive summarization task.