Results 1 to 10 of about 2,443,556 (65)
A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents [PDF]
North American Chapter of the Association for Computational Linguistics, 2018 Neural abstractive summarization models have led to promising results in summarizing relatively short documents. We propose the first model for abstractive summarization of single, longer-form documents (e.g., research papers). Our approach consists of a
Arman Cohan +6 more
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SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents [PDF]
AAAI Conference on Artificial Intelligence, 2016 We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence model for extractive summarization of documents and show that it achieves performance better than or comparable to state-of-the-art.
Ramesh Nallapati +2 more
semanticscholar +1 more source
FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents [PDF]
2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019 We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms. The dataset comprises 199 real, fully annotated, scanned forms.
Guillaume Jaume, H. K. Ekenel, J. Thiran
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Key-Value Memory Networks for Directly Reading Documents [PDF]
Conference on Empirical Methods in Natural Language Processing, 2016 Directly reading documents and being able to answer questions from them is an unsolved challenge. To avoid its inherent difficulty, question answering (QA) has been directed towards using Knowledge Bases (KBs) instead, which has proven effective ...
Alexander H. Miller +5 more
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TLDR: Extreme Summarization of Scientific Documents [PDF]
Findings, 2020 We introduce TLDR generation, a new form of extreme summarization, for scientific papers. TLDR generation involves high source compression and requires expert background knowledge and understanding of complex domain-specific language. To facilitate study
Isabel Cachola +3 more
semanticscholar +1 more source
Constructing Datasets for Multi-hop Reading Comprehension Across Documents [PDF]
Transactions of the Association for Computational Linguistics, 2017 Most Reading Comprehension methods limit themselves to queries which can be answered using a single sentence, paragraph, or document. Enabling models to combine disjoint pieces of textual evidence would extend the scope of machine comprehension methods ...
Johannes Welbl +2 more
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BiD: Textos Universitaris de Biblioteconomia i Documentació, 2010 Objectius. Analitzar l'existència i el contingut de documents de polítiques de col·lecció i criteris de selecció de les col·leccions digitals patrimonials espanyoles.
Estivill Rius, Assumpció +2 more
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Documents to the People, 2022 Introduction: A Brief Overview of Eugenics in the United States In recent years, debates centered around the idea and phenomenon of discrimination existing or being built directly into our governmental system(s), which is commonly referred to as ...
Teresa Lausell
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Text Mining: Use of TF-IDF to Examine the Relevance of Words to Documents
International Journal of Computer Applications, 2018 In this paper, the use of TF-IDF stands for (term frequencyinverse document frequency) is discussed in examining the relevance of key-words to documents in corpus. The study is focused on how the algorithm can be applied on number of documents.
Shahzad Qaiser, R. Ali
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A Hierarchical Neural Autoencoder for Paragraphs and Documents [PDF]
Annual Meeting of the Association for Computational Linguistics, 2015 Natural language generation of coherent long texts like paragraphs or longer documents is a challenging problem for recurrent networks models. In this paper, we explore an important step toward this generation task: training an LSTM (Longshort term ...
Jiwei Li, Minh-Thang Luong, Dan Jurafsky
semanticscholar +1 more source