[HTML][HTML] Automatic summarization of scientific articles: A survey

NI Altmami, MEB Menai - Journal of King Saud University-Computer and …, 2022‏ - Elsevier
The scientific research process generally starts with the examination of the state of the art,
which may involve a vast number of publications. Automatically summarizing scientific …

Automatic multiple choice question generation from text: A survey

DR Ch, SK Saha - IEEE Transactions on Learning …, 2018‏ - ieeexplore.ieee.org
Automatic multiple choice question (MCQ) generation from a text is a popular research area.
MCQs are widely accepted for large-scale assessment in various domains and applications …

Recursively summarizing books with human feedback

J Wu, L Ouyang, DM Ziegler, N Stiennon… - arxiv preprint arxiv …, 2021‏ - arxiv.org
A major challenge for scaling machine learning is training models to perform tasks that are
very difficult or time-consuming for humans to evaluate. We present progress on this …

HIBERT: Document level pre-training of hierarchical bidirectional transformers for document summarization

X Zhang, F Wei, M Zhou - arxiv preprint arxiv:1905.06566, 2019‏ - arxiv.org
Neural extractive summarization models usually employ a hierarchical encoder for
document encoding and they are trained using sentence-level labels, which are created …

Ranking sentences for extractive summarization with reinforcement learning

S Narayan, SB Cohen, M Lapata - arxiv preprint arxiv:1802.08636, 2018‏ - arxiv.org
Single document summarization is the task of producing a shorter version of a document
while preserving its principal information content. In this paper we conceptualize extractive …

A survey of automatic text summarization: Progress, process and challenges

MF Mridha, AA Lima, K Nur, SC Das, M Hasan… - IEEE …, 2021‏ - ieeexplore.ieee.org
With the evolution of the Internet and multimedia technology, the amount of text data has
increased exponentially. This text volume is a precious source of information and knowledge …

Neural summarization by extracting sentences and words

J Cheng, M Lapata - arxiv preprint arxiv:1603.07252, 2016‏ - arxiv.org
Traditional approaches to extractive summarization rely heavily on human-engineered
features. In this work we propose a data-driven approach based on neural networks and …

Recent automatic text summarization techniques: a survey

M Gambhir, V Gupta - Artificial Intelligence Review, 2017‏ - Springer
As information is available in abundance for every topic on internet, condensing the
important information in the form of summary would benefit a number of users. Hence, there …

Graph-based neural multi-document summarization

M Yasunaga, R Zhang, K Meelu, A Pareek… - arxiv preprint arxiv …, 2017‏ - arxiv.org
We propose a neural multi-document summarization (MDS) system that incorporates
sentence relation graphs. We employ a Graph Convolutional Network (GCN) on the relation …

Extractive summarization of long documents by combining global and local context

W **ao, G Carenini - arxiv preprint arxiv:1909.08089, 2019‏ - arxiv.org
In this paper, we propose a novel neural single document extractive summarization model
for long documents, incorporating both the global context of the whole document and the …