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Summarization

1,978 papers

Papers per year

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Papers

PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation EMNLP 2020
Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning EMNLP 2020
Multistage Fusion with Forget Gate for Multimodal Summarization in Open-Domain Videos EMNLP 2020
Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning EMNLP 2020
Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network EMNLP 2020
Coarse-to-Fine Query Focused Multi-Document Summarization EMNLP 2020
Pre-training for Abstractive Document Summarization by Reinstating Source Text EMNLP 2020
Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization EMNLP 2020
Few-Shot Learning for Opinion Summarization EMNLP 2020
Stepwise Extractive Summarization and Planning with Structured Transformers EMNLP 2020
Diverse, Controllable, and Keyphrase-Aware: A Corpus and Method for News Multi-Headline Generation EMNLP 2020
Factual Error Correction for Abstractive Summarization Models EMNLP 2020
Compressive Summarization with Plausibility and Salience Modeling EMNLP 2020
Understanding Neural Abstractive Summarization Models via Uncertainty EMNLP 2020
Better Highlighting: Creating Sub-Sentence Summary Highlights EMNLP 2020
Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach EMNLP 2020
Multi-hop Inference for Question-driven Summarization EMNLP 2020
TESA: A Task in Entity Semantic Aggregation for Abstractive Summarization EMNLP 2020
MLSUM: The Multilingual Summarization Corpus EMNLP 2020
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles EMNLP 2020
Intrinsic Evaluation of Summarization Datasets EMNLP 2020
PyMT5: multi-mode translation of natural language and Python code with transformers EMNLP 2020
On Extractive and Abstractive Neural Document Summarization with Transformer Language Models EMNLP 2020
Multi-Fact Correction in Abstractive Text Summarization EMNLP 2020
Evaluating the Factual Consistency of Abstractive Text Summarization EMNLP 2020