Papers Abstractive Text Summarization
“Abstractive Text Summarization” 태그가 달린 논문 852편 · 필터 해제
Unsupervised Multi-Granularity Summarization
Text summarization is a user-preference based task. For one document, users often have different priorities for summary. Granularity level of the summary is a core component of these preferences. However, most existing s…
Abstractive Text SummarizationText SummarizationGenerating Diverse and High-Quality Abstractive Summaries with Variational Transformers
Existing works on abstractive summarization mainly focus on boosting summarization's quality (informativeness, contextual similarity). To generate summaries of both high diversity and quality, we proposes the Transformer…
Abstractive Text SummarizationDecoderDiversityInformativeness+1A Unified and Efficient Contrastive Learning Framework for Text Summarization
Both extractive and abstractive summarization systems share a common problem, i.e., there is a mismatch between the training object and evaluation metrics. To bridge this gap, we introduce a unified and efficient contra…
Abstractive Text SummarizationContrastive LearningText SummarizationIncorporating Question Answering-Based Signals into Abstractive Summarization via Salient Span Selection
In this work, we propose a method for incorporating question-answering (QA) signals into a summarization model. Our method identifies salient noun phrases (NPs) in the input document by automatically generating wh-questi…
Abstractive Text SummarizationQuestion AnsweringText SummarizationSummarization of German Court Rulings
Historically speaking, the German legal language is widely neglected in NLP research, especially in summarization systems, as most of them are based on English newspaper articles. In this paper, we propose the task of au…
Abstractive Text SummarizationArticlesUsing Question Answering Rewards to Improve Abstractive Summarization
Neural abstractive summarization models have drastically improved in the recent years. However, the summaries generated by these models generally suffer from issues such as: not capturing the critical facts in source doc…
Abstractive Text SummarizationQuestion AnsweringA Finer-grain Universal Dialogue Semantic Structures based Model For Abstractive Dialogue Summarization
Although abstractive summarization models have achieved impressive results on document summarization tasks, their performance on dialogue modeling is much less satisfactory due to the crude and straight methods for dialo…
Abstractive Dialogue SummarizationAbstractive Text SummarizationDocument SummarizationExploring Multitask Learning for Low-Resource Abstractive Summarization
This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different tasks (extractive summarization, language mo…
Abstractive Text SummarizationExtractive SummarizationLanguage ModelingLanguage ModellingForumSum: A Multi-Speaker Conversation Summarization Dataset
Abstractive summarization quality had large improvements since recent language pretraining techniques. However, currently there is a lack of datasets for the growing needs of conversation summarization applications. Thus…
Abstractive Text SummarizationConversation SummarizationFine-grained Factual Consistency Assessment for Abstractive Summarization Models
Factual inconsistencies existed in the output of abstractive summarization models with original documents are frequently presented. Fact consistency assessment requires the reasoning capability to find subtle clues to id…
Abstractive Text SummarizationSentenceIntegrating Semantic Scenario and Word Relations for Abstractive Sentence Summarization
Recently graph-based methods have been adopted for Abstractive Text Summarization. However, existing graph-based methods only consider either word relations or structure information, which neglect the correlation between…
Abstractive Text SummarizationSentenceSentence SummarizationText SummarizationEvent Graph based Sentence Fusion
Sentence fusion is a conditional generation task that merges several related sentences into a coherent one, which can be deemed as a summary sentence. The importance of sentence fusion has long been recognized by communi…
Abstractive Text SummarizationSentenceSentence FusionText Generation+1Learn to Copy from the Copying History: Correlational Copy Network for Abstractive Summarization
The copying mechanism has had considerable success in abstractive summarization, facilitating models to directly copy words from the input text to the output summary. Existing works mostly employ encoder-decoder attentio…
Abstractive Text SummarizationDecoderNews SummarizationGradient-Based Adversarial Factual Consistency Evaluation for Abstractive Summarization
Neural abstractive summarization systems have gained significant progress in recent years. However, abstractive summarization often produce inconsisitent statements or false facts. How to automatically generate highly ab…
Abstractive Text SummarizationData AugmentationGupShup: Summarizing Open-Domain Code-Switched Conversations
Code-switching is the communication phenomenon where the speakers switch between different languages during a conversation. With the widespread adoption of conversational agents and chat platforms, code-switching has bec…
Abstractive Text SummarizationConversation SummarizationQ^{2}: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering
Neural knowledge-grounded generative models for dialogue often produce content that is factually inconsistent with the knowledge they rely on, making them unreliable and limiting their applicability. Inspired by recent w…
Abstractive Text SummarizationNatural Language InferenceQuestion AnsweringQuestion Generation+1AUTOSUMM: Automatic Model Creation for Text Summarization
Recent efforts to develop deep learning models for text generation tasks such as extractive and abstractive summarization have resulted in state-of-the-art performances on various datasets. However, obtaining the best mo…
Abstractive Text SummarizationDeep LearningKnowledge Distillationmodel+3Sentence-level Planning for Especially Abstractive Summarization
Abstractive summarization models heavily rely on copy mechanisms, such as the pointer network or attention, to achieve good performance, measured by textual overlap with reference summaries. As a result, the generated su…
Abstractive Text SummarizationDecoderSentenceRewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization
We consider the problem of topic-focused abstractive summarization, where the goal is to generate an abstractive summary focused on a particular topic, a phrase of one or multiple words. We hypothesize that the task of g…
Abstractive Text SummarizationDeep Reinforcement LearningReinforcement Learning (RL)A Novel Wikipedia based Dataset for Monolingual and Cross-Lingual Summarization
Cross-lingual summarization is a challenging task for which there are no cross-lingual scientific resources currently available. To overcome the lack of a high-quality resource, we present a new dataset for monolingual a…
Abstractive Text SummarizationArticles