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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 – 3 of 3 1 EASE: Extractive-Abstractive Summarization End-to-End using the Information Bottleneck Principle ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Srinivasan; Einolghozati, Arash; Ghazvininejad, Marjan; Gupta, Sonal; Li, Haoran; Mehdad, Yashar; Paranjape, Bhargavi. - : Underline Science Inc., 2021 Abstract: Current abstractive summarization systems outperform their extractive counterparts, but their widespread adoption is inhibited by the inherent lack of interpretability. Extractive summarization systems, though interpretable, suffer from redundancy and possible lack of coherence. To achieve the best of both worlds, we propose EASE, an extractive-abstractive framework that generates concise abstractive summaries that can be traced back to an extractive summary. Our framework can be applied to any evidence-based text generation problem and can accommodate various pretrained models in its simple architecture. We use the Information Bottleneck principle to jointly train the extraction and abstraction in an end-to-end fashion. Inspired by previous research that humans use a two-stage framework to summarize long documents (Jing and McKeown, 2000), our framework first extracts a pre-defined amount of evidence spans and then generates a summary using only the evidence. Using automatic and human evaluations, we show ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Text Summarization URL: https://dx.doi.org/10.48448/dvcn-0n74 https://underline.io/lecture/39828-ease-extractive-abstractive-summarization-end-to-end-using-the-information-bottleneck-principle BASE Hide details 2 ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining ... 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; Fabbri, Alexander; Li, Haoran. - : Underline Science Inc., 2021 BASE Show details 3 Syntax-augmented Multilingual BERT for Cross-lingual Transfer ... 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; Ahmad, Wasi Uddin; Chang, Kai-Wei. - : Underline Science Inc., 2021 BASE Show details

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