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[HTML][HTML] Automatic summarization of scientific articles: A survey
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 …
which may involve a vast number of publications. Automatically summarizing scientific …
Automatic multiple choice question generation from text: A survey
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 …
MCQs are widely accepted for large-scale assessment in various domains and applications …
Recursively summarizing books with human feedback
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 …
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
Neural extractive summarization models usually employ a hierarchical encoder for
document encoding and they are trained using sentence-level labels, which are created …
document encoding and they are trained using sentence-level labels, which are created …
Ranking sentences for extractive summarization with reinforcement learning
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 …
while preserving its principal information content. In this paper we conceptualize extractive …
A survey of automatic text summarization: Progress, process and challenges
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 …
increased exponentially. This text volume is a precious source of information and knowledge …
Neural summarization by extracting sentences and words
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 …
features. In this work we propose a data-driven approach based on neural networks and …
Recent automatic text summarization techniques: a survey
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 …
important information in the form of summary would benefit a number of users. Hence, there …
Graph-based neural multi-document summarization
We propose a neural multi-document summarization (MDS) system that incorporates
sentence relation graphs. We employ a Graph Convolutional Network (GCN) on the relation …
sentence relation graphs. We employ a Graph Convolutional Network (GCN) on the relation …
Extractive summarization of long documents by combining global and local context
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 …
for long documents, incorporating both the global context of the whole document and the …