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Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.
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.
Dataset and Codes for our EMNLP 2022 Main Conference Long Paper titled "ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcripts"
Klexikon: A German Dataset for Joint Summarization and Simplification
Code and data for the Dreyer et al (2023) paper on abstractiveness and factuality in abstractive summarization
This is the official PyTorch codebase for the ACL 2023 paper: "What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization".
Thai Crosslingual Summarization Datasets.
[EACL 2021] - Unsupervised Abstractive Summarization of Bengali Text Documents.
[Computer Speech & Language, Elsevier] - Neural Sentence Fusion for Diversity Driven Abstractive Multi-Document Summarization.
In deep learning NLP, using a model we are trying to summarization the text.
M3LS : Multi-lingual Multi-modal summarization dataset
Dataset for abstractive summarization of long multimodal presentations
Specific-Aspect Summarization on News According to Social Sentiments on Twitter