Abstractive

AbstractAutomatic summarization is typically treated as a 1-to-1 mapping from document to summary. Documents such as news articles, however, are structured and often cover multiple topics or aspects; and readers …...

AbstractAutomated evaluation metrics as a stand-in for manual evaluation are an essential part of the development of text-generation tasks such as text summarization. However, while the field has progressed, our …...

AbstractOpinion summarization is the task of automatically creating summaries that reflect subjective information expressed in multiple documents, such as product reviews. While the majority of previous work has focused on …...

ive Dialogue Summarization with Sketch Supervision Chien-Sheng Wu∗1, Linqing Liu∗2, Wenhao Liu1, Pontus Stenetorp2, Caiming Xiong1 1 Salesforce Research 2 University College London {linqing.liu,p.stenetorp}@cs.ucl.ac.uk, {wu.jason, wenhao.liu, cxiong}@salesforce.com Abstract In this …...

State-of-the-art summarization systems are trained and evaluated on massive datasets scraped from the web. Despite their preva- lence, we know very little about the underly- ing characteristics (data noise, summarization …...

AbstractModel-based, reference-free evaluation metricshave been proposed as a fast and cost-effectiveapproach to evaluate Natural Language Generation(NLG) systems. Despite promising recentresults, we find evidence that reference-freeevaluation metrics of summarization and dialoggeneration …...

AbstractWe introduce the task of microblog opinion summarization (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain. The dataset contains summaries of tweets …...