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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. - : Underline Science Inc., 2021 BASE Show 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; Rothe, Sascha. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.12/ Abstract: Task-agnostic pretraining objectives like masked language models or corrupted span prediction are applicable to a wide range of NLP downstream tasks (Raffel et al., 2019), but are outperformed by task-specific pretraining objectives like predicting extracted gap sentences on summarization (Zhang et al., 2020). We compare three summarization specific pretraining objectives with the task agnostic corrupted span prediction pretraining in a controlled study. We also extend our study to a low resource and zero shot setup, to understand how many training examples are needed in order to ablate the task-specific pretraining without quality loss. Our results show that task-agnostic pretraining is sufficient for most cases which hopefully reduces the need for costly task-specific pretraining. We also report new state-of-the-art number for two summarization tasks using a T5 model with 11 billion parameters and an optimal beam search length ... Keyword: Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Text Summarization URL: https://dx.doi.org/10.48448/rxsd-pa23 https://underline.io/lecture/38078-a-thorough-evaluation-of-task-specific-pretraining-for-summarization BASE Hide 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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