Attend , Translate and Summarize : An Efficient Method for Neural Cross-Lingual Summarization
Discourse - Aware Neural Extractive Text Summarization
Discrete Optimization for Unsupervised Sentence Summarization with Word - Level Extraction
Examining the State-of-the-Art in News Timeline Summarization
Extractive Summarization as Text Matching
Facet-Aware Evaluation for Extractive Summarization
FEQA : A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization
From Arguments to Key Points : Towards Automatic Argument Summarization
Heterogeneous Graph Neural Networks for Extractive Document Summarization
Jointly Learning to Align and Summarize for Neural Cross-Lingual Summarization
Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward
Leveraging Graph to Improve Abstractive Multi-Document Summarization
MATINF : A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization
Multi-Granularity Interaction Network for Extractive and Abstractive Multi-Document Summarization
On Faithfulness and Factuality in Abstractive Summarization
Screenplay Summarization Using Latent Narrative Structure
Unsupervised Opinion Summarization as Copycat-Review Generation
Unsupervised Opinion Summarization with Noising and Denoising
A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal
Attend to Medical Ontologies : Content Selection for Clinical Abstractive Summarization
Composing Elementary Discourse Units in Abstractive Summarization
Exploring Content Selection in Summarization of Novel Chapters
OpinionDigest : A Simple Framework for Opinion Summarization
Self-Attention Guided Copy Mechanism for Abstractive Summarization
SUPERT : Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarization
Understanding Points of Correspondence between Sentences for Abstractive Summarization
Asking and Answering Questions to Evaluate the Factual Consistency of Summaries
Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports [arXiv]
The Summary Loop: Learning to Write Abstractive Summaries Without Examples
Fact based Content Weighting for Evaluating Abstractive Summarisation