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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Dusek, Ondrej; Konstas, Ioannis; Narayan, Shashi; Rieser, Verena; Xu, Xinnuo. - : Underline Science Inc., 2021 Abstract: One of the most challenging aspects of current single-document news summarization is that the summary often contains 'extrinsic hallucinations', i.e., facts that are not present in the source document, which are often derived via world knowledge. This causes summarization systems to act more like open-ended language models tending to hallucinate facts that are erroneous. In this paper, we mitigate this problem with the help of multiple supplementary resource documents assisting the task. We present a new dataset MiRANews and benchmark existing summarization models. In contrast to multi-document summarization, which addresses multiple events from several source documents, we still aim at generating a summary for a single document. We show via data analysis that it's not only the models which are to blame: more than 27% of facts mentioned in the gold summaries of MiRANews are better grounded on assisting documents than in the main source articles. An error analysis of generated summaries from pretrained models ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Text Summarization URL: https://underline.io/lecture/39839-miranews-dataset-and-benchmarks-for-multi-resource-assisted-news-summarization https://dx.doi.org/10.48448/ef01-yt90 BASE Hide details 2 AugNLG: Few-shot Natural Language Generation using Self-trained Data Augmentation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Xu, Xinnuo. - : Underline Science Inc., 2021 BASE Show details 3 AggGen: Ordering and Aggregating while Generating ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Dusek, Ondrej; Konstas, Ioannis. - : Underline Science Inc., 2021 BASE Show details 4 Better Conversations by Modeling,Filtering,and Optimizing for Coherence and Diversity ... Xu, Xinnuo; Dušek, Ondřej; Konstas, Ioannis. - : arXiv, 2018 BASE Show details

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