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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 – 12 of 12 1 HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; He, Lifang; LIU, YE. - : Underline Science Inc., 2021 BASE Show details 2 CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cao, Shuyang; Wang, Lu. - : Underline Science Inc., 2021 BASE Show details 3 Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Dai, Wenliang; Fung, Pascale; Liu, Zihan; yu, volunteerTiezheng. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.326/ Abstract: Multimodal abstractive summarization (MAS) aims to take advantage of data from multiple modalities and provides a short, concise and readable textual summary to let users quickly acquire their essential information. Recently, large-scale generative pre-trained language models (GPLMs) have shown remarkable performance on abstractive text summarization. However, leveraging and adapting GPLMs to MAS is still an unexplored research direction. Our contributions in this work are threefold: 1. To the best of our knowledge, we are the first to inject visual information into text-only GPLMs, and to use it for the MAS task. 2. We systematically study two research questions: 1) how to inject visual information into GPLMs without hurting their generation ability; and 2) where is the optimal place in GPLMs to inject the visual information? 3. Our model significantly outperforms the state-of-the-art model on the How2 dataset, and the injected ... Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Text Summarization URL: https://underline.io/lecture/37583-vision-guided-generative-pre-trained-language-models-for-multimodal-abstractive-summarization https://dx.doi.org/10.48448/m679-m796 BASE Hide details 4 A Thorough Evaluation of Task-Specific Pretraining for Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Maynez, Joshua; Narayan, Shashi. - : Underline Science Inc., 2021 BASE Show details 5 Effective Sequence-to-Sequence Dialogue State Tracking ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cao, Yuan; Mahdieh, Mahdis. - : Underline Science Inc., 2021 BASE Show details 6 Capturing Speaker Incorrectness: Speaker-Focused Post-Correction for Abstractive Dialogue Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Lee, Dongyub. - : Underline Science Inc., 2021 BASE Show details 7 AUTOSUMM: Automatic Model Creation for Text Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chhaya, Niyati; Nangi, Sharmila Reddy. - : Underline Science Inc., 2021 BASE Show details 8 A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Deutsch, Daniel. - : Underline Science Inc., 2021 BASE Show details 9 A Novel Wikipedia based Dataset for Monolingual and Cross-Lingual Summarization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Fatima, Mehwish; Strube, Michael. - : Underline Science Inc., 2021 BASE Show details 10 Measuring Similarity of Opinion-bearing Sentences ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Stephen; Karimi, Sarvnaz. - : Underline Science Inc., 2021 BASE Show details 11 A New Dataset and Efficient Baselines for Document-level Text Simplification in German ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ebling, Sarah; Kew, Tannon. - : Underline Science Inc., 2021 BASE Show details 12 Towards Syntax-Aware DialogueSummarization using Multi-task Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Lee, Seolhwa; Lim, Heuiseok. - : Underline Science Inc., 2021 BASE Show details

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