Summarization of legal documents: Where are we now and the way forward
Due to huge amount of legal information availability on the internet, as well as other sources,
it is important for the research community to do more extensive research on the area of legal …
it is important for the research community to do more extensive research on the area of legal …
A comprehensive survey of abstractive text summarization based on deep learning
M Zhang, G Zhou, W Yu, N Huang… - Computational …, 2022 - Wiley Online Library
With the rapid development of the Internet, the massive amount of web textual data has
grown exponentially, which has brought considerable challenges to downstream tasks, such …
grown exponentially, which has brought considerable challenges to downstream tasks, such …
Bottom-up abstractive summarization
Neural network-based methods for abstractive summarization produce outputs that are more
fluent than other techniques, but which can be poor at content selection. This work proposes …
fluent than other techniques, but which can be poor at content selection. This work proposes …
Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Automatic generation of summaries from multiple news articles is a valuable tool as the
number of online publications grows rapidly. Single document summarization (SDS) …
number of online publications grows rapidly. Single document summarization (SDS) …
Neural text summarization: A critical evaluation
Text summarization aims at compressing long documents into a shorter form that conveys
the most important parts of the original document. Despite increased interest in the …
the most important parts of the original document. Despite increased interest in the …
On extractive and abstractive neural document summarization with transformer language models
We present a method to produce abstractive summaries of long documents that exceed
several thousand words via neural abstractive summarization. We perform a simple …
several thousand words via neural abstractive summarization. We perform a simple …
A unified model for extractive and abstractive summarization using inconsistency loss
WT Hsu, CK Lin, MY Lee, K Min, J Tang… - arXiv preprint arXiv …, 2018 - arxiv.org
We propose a unified model combining the strength of extractive and abstractive
summarization. On the one hand, a simple extractive model can obtain sentence-level …
summarization. On the one hand, a simple extractive model can obtain sentence-level …
DeepSumm: Exploiting topic models and sequence to sequence networks for extractive text summarization
In this paper, we propose DeepSumm, a novel method based on topic modeling and word
embeddings for the extractive summarization of single documents. Recent summarization …
embeddings for the extractive summarization of single documents. Recent summarization …
[HTML][HTML] Summarization of scholarly articles using BERT and BiGRU: Deep learning-based extractive approach
Extractive text summarization involves selecting and combining key sentences directly from
the original text, rather than generating new content. While various methods, both statistical …
the original text, rather than generating new content. While various methods, both statistical …
A divide-and-conquer approach to the summarization of long documents
A Gidiotis, G Tsoumakas - IEEE/ACM Transactions on Audio …, 2020 - ieeexplore.ieee.org
We present a novel divide-and-conquer method for the neural summarization of long
documents. Our method exploits the discourse structure of the document and uses sentence …
documents. Our method exploits the discourse structure of the document and uses sentence …