Papers Sentence Summarization
“Sentence Summarization” 태그가 달린 논문 44편 · 필터 해제
Show, Tell and Summarize: Dense Video Captioning Using Visual Cue Aided Sentence Summarization
In this work, we propose a division-and-summarization (DaS) framework for dense video captioning. After partitioning each untrimmed long video as multiple event proposals, where each event proposal consists of a set of s…
Dense Video CaptioningDescriptiveSentenceSentence Summarization+1Dense Video Captioning using Graph-based Sentence Summarization
Recently, dense video captioning has made attractive progress in detecting and captioning all events in a long untrimmed video. Despite promising results were achieved, most existing methods do not sufficiently explore t…
Dense Video CaptioningSentenceSentence SummarizationVideo CaptioningImpossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing
We present Impossible Distillation, a novel framework for paraphrasing and sentence summarization, that distills a high-quality dataset and model from a low-quality teacher that itself cannot perform these tasks. Unlike …
DiversitymodelParaphrase GenerationSentence+1Generating Multiple-Length Summaries via Reinforcement Learning for Unsupervised Sentence Summarization
Sentence summarization shortens given texts while maintaining core contents of the texts. Unsupervised approaches have been studied to summarize texts without human-written summaries. However, recent unsupervised models …
Abstractive Text Summarizationreinforcement-learningReinforcement Learning (RL)Sentence+2Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation
We present Referee, a novel framework for sentence summarization that can be trained reference-free (i.e., requiring no gold summaries for supervision), while allowing direct control for compression ratio. Our work is th…
Knowledge DistillationSentenceSentence SummarizationA Character-Level Length-Control Algorithm for Non-Autoregressive Sentence Summarization
Sentence summarization aims at compressing a long sentence into a short one that keeps the main gist, and has extensive real-world applications such as headline generation. In previous work, researchers have developed va…
Headline GenerationSentenceSentence SummarizationLearning Non-Autoregressive Models from Search for Unsupervised Sentence Summarization
Text summarization aims to generate a short summary for an input text. In this work, we propose a Non-Autoregressive Unsupervised Summarization (NAUS) approach, which does not require parallel data for training. Our NAUS…
SentenceSentence SummarizationText SummarizationUnsupervised Sentence SummarizationIndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages
Natural Language Generation (NLG) for non-English languages is hampered by the scarcity of datasets in these languages. In this paper, we present the IndicNLG Benchmark, a collection of datasets for benchmarking NLG for …
ArticlesBenchmarkingHeadline GenerationMachine Translation+6Extract, Select and Rewrite: A New Modular Summarization Method
Prior works on supervised summarization are mainly based on end-to-end models, leading to low modularity, unfaithfulness and low interpretability. To address this, we propose a new three-phase modular abstractive sentenc…
SentenceSentence SummarizationLearning Non-Autoregressive Models from Search for Unsupervised Sentence Summarization
Text summarization aims to generate a short summary for an input text. In this work, we propose a Non-Autoregressive Unsupervised Summarization (NAUS) approach, which does not require parallel data for training. Our NAUS…
Headline GenerationSentenceSentence SummarizationText Summarization+1Integrating 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 SummarizationKnowledge and Keywords Augmented Abstractive Sentence Summarization
In this paper, we study the abstractive sentence summarization. There are two essential information features that can influence the quality of news summarization, which are topic keywords and the knowledge structure of t…
News SummarizationSentenceSentence SummarizationBag-of-Vectors Autoencoders for Unsupervised Conditional Text Generation
Text autoencoders are often used for unsupervised conditional text generation by applying mappings in the latent space to change attributes to the desired values. Recently, Mai et al. (2020) proposed Emb2Emb, a method to…
Conditional Text GenerationSentence SummarizationText GenerationICAF: Iterative Contrastive Alignment Framework for Multimodal Abstractive Summarization
Integrating multimodal knowledge for abstractive summarization task is a work-in-progress research area, with present techniques inheriting fusion-then-generation paradigm. Due to semantic gaps between computer vision an…
Abstractive Text SummarizationSentence SummarizationCoNFET: An English Sentence to Emojis Translation Algorithm
Emojis are a collection of emoticons that have been standardized by the Unicode Consortium. Currently, there are over 3,000 emojis in the Unicode standard. These small pictographs can represent an object as vague as a l…
Natural Language UnderstandingSentenceSentence SummarizationTranslationMultimodal Sentence Summarization via Multimodal Selective Encoding
This paper studies the problem of generating a summary for a given sentence-image pair. Existing multimodal sequence-to-sequence approaches mainly focus on enhancing the decoder by visual signals, while ignoring that the…
DecoderSentenceSentence SummarizationControllable Abstractive Sentence Summarization with Guiding Entities
Entities are the major proportion and build up the topic of text summaries. Although existing text summarization models can produce promising results of automatic metrics, for example, ROUGE, it is difficult to guarantee…
InformativenessSentenceSentence SummarizationText SummarizationMulti-Image Summarization: Textual Summary from a Set of Cohesive Images
Multi-sentence summarization is a well studied problem in NLP, while generating image descriptions for a single image is a well studied problem in Computer Vision. However, for applications such as image cluster labeling…
DescriptiveImage CaptioningSentenceSentence SummarizationDiscrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction
Automatic sentence summarization produces a shorter version of a sentence, while preserving its most important information. A good summary is characterized by language fluency and high information overlap with the source…
Language ModelingLanguage ModellingSemantic SimilaritySemantic Textual Similarity+3All Word Embeddings from One Embedding
In neural network-based models for natural language processing (NLP), the largest part of the parameters often consists of word embeddings. Conventional models prepare a large embedding matrix whose size depends on the v…
AllDecoderMachine TranslationSentence Summarization+3