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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 – 5 of 5 1 Sparsity and Sentence Structure in Encoder-Decoder Attention of Summarization Systems ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gales, Mark; Manakul, Potsawee. - : Underline Science Inc., 2021 BASE Show details 2 Sparsity and Sentence Structure in Encoder-Decoder Attention of Summarization Systems ... Manakul, Potsawee; Gales, Mark. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 3 Sparsity and Sentence Structure in Encoder-Decoder Attention of Summarization Systems ... Manakul, Potsawee; Gales, Mark J. F.. - : arXiv, 2021 Abstract: Transformer models have achieved state-of-the-art results in a wide range of NLP tasks including summarization. Training and inference using large transformer models can be computationally expensive. Previous work has focused on one important bottleneck, the quadratic self-attention mechanism in the encoder. Modified encoder architectures such as LED or LoBART use local attention patterns to address this problem for summarization. In contrast, this work focuses on the transformer's encoder-decoder attention mechanism. The cost of this attention becomes more significant in inference or training approaches that require model-generated histories. First, we examine the complexity of the encoder-decoder attention. We demonstrate empirically that there is a sparse sentence structure in document summarization that can be exploited by constraining the attention mechanism to a subset of input sentences, whilst maintaining system performance. Second, we propose a modified architecture that selects the subset of ... : EMNLP 2021 (short paper, main conference) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2109.03888 https://dx.doi.org/10.48550/arxiv.2109.03888 BASE Hide details 4 Long-Span Summarization via Local Attention and Content Selection ... 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; Gales, Mark; Manakul, Potsawee. - : Underline Science Inc., 2021 BASE Show details 5 Long-span summarization via local attention and content selection Manakul, Potsawee; Gales, Mark. - : ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2021 BASE Show details

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