Paper Group NANR 140
Cascaded Attention based Unsupervised Information Distillation for Compressive Summarization. Interactive Abstractive Summarization for Event News Tweets. Wheel of Life: an initial investigation. Topic-Related Polarity Visualization in Personal Stories. Data-driven Morphology and Sociolinguistics for Early Modern Dutch. Services for text simplifica …
Cascaded Attention based Unsupervised Information Distillation for Compressive Summarization
Title | Cascaded Attention based Unsupervised Information Distillation for Compressive Summarization |
Authors | Piji Li, Wai Lam, Lidong Bing, Weiwei Guo, Hang Li |
Abstract | When people recall and digest what they have read for writing summaries, the important content is more likely to attract their attention. Inspired by this observation, we propose a cascaded attention based unsupervised model to estimate the salience information from the text for compressive multi-document summarization. The attention weights are learned automatically by an unsupervised data reconstruction framework which can capture the sentence salience. By adding sparsity constraints on the number of output vectors, we can generate condensed information which can be treated as word salience. Fine-grained and coarse-grained sentence compression strategies are incorporated to produce compressive summaries. Experiments on some benchmark data sets show that our framework achieves better results than the state-of-the-art methods. |
Tasks | Document Summarization, Multi-Document Summarization, Sentence Compression |
Published | 2017-09-01 |
URL | https://www.aclweb.org/anthology/D17-1221/ |
https://www.aclweb.org/anthology/D17-1221 | |
PWC | https://paperswithcode.com/paper/cascaded-attention-based-unsupervised |
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Interactive Abstractive Summarization for Event News Tweets
Title | Interactive Abstractive Summarization for Event News Tweets |
Authors | Ori Shapira, Hadar Ronen, Meni Adler, Yael Amsterdamer, Judit Bar-Ilan, Ido Dagan |
Abstract | We present a novel interactive summarization system that is based on abstractive summarization, derived from a recent consolidated knowledge representation for multiple texts. We incorporate a couple of interaction mechanisms, providing a bullet-style summary while allowing to attain the most important information first and interactively drill down to more specific details. A usability study of our implementation, for event news tweets, suggests the utility of our approach for text exploration. |
Tasks | Abstractive Text Summarization, Document Summarization, Multi-Document Summarization |
Published | 2017-09-01 |
URL | https://www.aclweb.org/anthology/D17-2019/ |
https://www.aclweb.org/anthology/D17-2019 | |
PWC | https://paperswithcode.com/paper/interactive-abstractive-summarization-for |
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Wheel of Life: an initial investigation. Topic-Related Polarity Visualization in Personal Stories
Title | Wheel of Life: an initial investigation. Topic-Related Polarity Visualization in Personal Stories |
Authors | Henrique Santos, Renata Vieira, Greice Pinho, Jackson Pinheiro |
Abstract | |
Tasks | Information Retrieval, Sentiment Analysis |
Published | 2017-10-01 |
URL | https://www.aclweb.org/anthology/W17-6606/ |
https://www.aclweb.org/anthology/W17-6606 | |
PWC | https://paperswithcode.com/paper/wheel-of-life-an-initial-investigation-topic |
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Data-driven Morphology and Sociolinguistics for Early Modern Dutch
Title | Data-driven Morphology and Sociolinguistics for Early Modern Dutch |
Authors | Marijn Schraagen, Marjo van Koppen, Feike Dietz |
Abstract | |
Tasks | |
Published | 2017-05-01 |
URL | https://www.aclweb.org/anthology/W17-0509/ |
https://www.aclweb.org/anthology/W17-0509 | |
PWC | https://paperswithcode.com/paper/data-driven-morphology-and-sociolinguistics |
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Services for text simplification and analysis
Title | Services for text simplification and analysis |
Authors | Johan Falkenjack, Evelina Rennes, Daniel Fahlborg, Vida Johansson, Arne J{"o}nsson |
Abstract | |
Tasks | Lemmatization, Text Simplification, Text Summarization, Tokenization |
Published | 2017-05-01 |
URL | https://www.aclweb.org/anthology/W17-0244/ |
https://www.aclweb.org/anthology/W17-0244 | |
PWC | https://paperswithcode.com/paper/services-for-text-simplification-and-analysis |
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Textual Relations and Topic-Projection: Issues in Text Categorization
Title | Textual Relations and Topic-Projection: Issues in Text Categorization |
Authors | Lahari Chatterjee, Samir Karmakar, Abahan Datta |
Abstract | |
Tasks | Text Categorization |
Published | 2017-12-01 |
URL | https://www.aclweb.org/anthology/W17-7506/ |
https://www.aclweb.org/anthology/W17-7506 | |
PWC | https://paperswithcode.com/paper/textual-relations-and-topic-projection-issues |
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Fader Networks:Manipulating Images by Sliding Attributes
Title | Fader Networks:Manipulating Images by Sliding Attributes |
Authors | Guillaume Lample, Neil Zeghidour, Nicolas Usunier, Antoine Bordes, Ludovic Denoyer, Marc’Aurelio Ranzato |
Abstract | This paper introduces a new encoder-decoder architecture that is trained to reconstruct images by disentangling the salient information of the image and the values of attributes directly in the latent space. As a result, after training, our model can generate different realistic versions of an input image by varying the attribute values. By using continuous attribute values, we can choose how much a specific attribute is perceivable in the generated image. This property could allow for applications where users can modify an image using sliding knobs, like faders on a mixing console, to change the facial expression of a portrait, or to update the color of some objects. Compared to the state-of-the-art which mostly relies on training adversarial networks in pixel space by altering attribute values at train time, our approach results in much simpler training schemes and nicely scales to multiple attributes. We present evidence that our model can significantly change the perceived value of the attributes while preserving the naturalness of images. |
Tasks | |
Published | 2017-12-01 |
URL | http://papers.nips.cc/paper/7178-fader-networksmanipulating-images-by-sliding-attributes |
http://papers.nips.cc/paper/7178-fader-networksmanipulating-images-by-sliding-attributes.pdf | |
PWC | https://paperswithcode.com/paper/fader-networksmanipulating-images-by-sliding |
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SGM-Nets: Semi-Global Matching With Neural Networks
Title | SGM-Nets: Semi-Global Matching With Neural Networks |
Authors | Akihito Seki, Marc Pollefeys |
Abstract | This paper deals with deep neural networks for predicting accurate dense disparity map with Semi-global matching (SGM). SGM is a widely used regularization method for real scenes because of its high accuracy and fast computation speed. Even though SGM can obtain accurate results, tuning of SGM’s penalty-parameters, which control a smoothness and discontinuity of a disparity map, is uneasy and empirical methods have been proposed. We propose a learning based penalties estimation method, which we call SGM-Nets that consist of Convolutional Neural Networks. A small image patch and its position are input into SGMNets to predict the penalties for the 3D object structures. In order to train the networks, we introduce a novel loss function which is able to use sparsely annotated disparity maps such as captured by a LiDAR sensor in real environments. Moreover, we propose a novel SGM parameterization, which deploys different penalties depending on either positive or negative disparity changes in order to represent the object structures more discriminatively. Our SGM-Nets outperformed state of the art accuracy on KITTI benchmark datasets. |
Tasks | |
Published | 2017-07-01 |
URL | http://openaccess.thecvf.com/content_cvpr_2017/html/Seki_SGM-Nets_Semi-Global_Matching_CVPR_2017_paper.html |
http://openaccess.thecvf.com/content_cvpr_2017/papers/Seki_SGM-Nets_Semi-Global_Matching_CVPR_2017_paper.pdf | |
PWC | https://paperswithcode.com/paper/sgm-nets-semi-global-matching-with-neural |
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Languages under the influence: Building a database of Uralic languages
Title | Languages under the influence: Building a database of Uralic languages |
Authors | Eszter Simon, Nikolett Mus |
Abstract | |
Tasks | |
Published | 2017-01-01 |
URL | https://www.aclweb.org/anthology/W17-0603/ |
https://www.aclweb.org/anthology/W17-0603 | |
PWC | https://paperswithcode.com/paper/languages-under-the-influence-building-a |
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Learning Antonyms with Paraphrases and a Morphology-Aware Neural Network
Title | Learning Antonyms with Paraphrases and a Morphology-Aware Neural Network |
Authors | Sneha Rajana, Chris Callison-Burch, Marianna Apidianaki, Vered Shwartz |
Abstract | Recognizing and distinguishing antonyms from other types of semantic relations is an essential part of language understanding systems. In this paper, we present a novel method for deriving antonym pairs using paraphrase pairs containing negation markers. We further propose a neural network model, AntNET, that integrates morphological features indicative of antonymy into a path-based relation detection algorithm. We demonstrate that our model outperforms state-of-the-art models in distinguishing antonyms from other semantic relations and is capable of efficiently handling multi-word expressions. |
Tasks | Semantic Textual Similarity, Word Embeddings |
Published | 2017-08-01 |
URL | https://www.aclweb.org/anthology/S17-1002/ |
https://www.aclweb.org/anthology/S17-1002 | |
PWC | https://paperswithcode.com/paper/learning-antonyms-with-paraphrases-and-a |
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A Comparative Study for Sentiment Analysis on Election Brazilian News
Title | A Comparative Study for Sentiment Analysis on Election Brazilian News |
Authors | Caio Magno Aguiar Carvalho, Hitoshi Nagano, Allan Kardec Barros |
Abstract | |
Tasks | Sentiment Analysis |
Published | 2017-10-01 |
URL | https://www.aclweb.org/anthology/W17-6613/ |
https://www.aclweb.org/anthology/W17-6613 | |
PWC | https://paperswithcode.com/paper/a-comparative-study-for-sentiment-analysis-on |
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A Multi-View Sentiment Corpus
Title | A Multi-View Sentiment Corpus |
Authors | Debora Nozza, Elisabetta Fersini, Enza Messina |
Abstract | Sentiment Analysis is a broad task that involves the analysis of various aspect of the natural language text. However, most of the approaches in the state of the art usually investigate independently each aspect, i.e. Subjectivity Classification, Sentiment Polarity Classification, Emotion Recognition, Irony Detection. In this paper we present a Multi-View Sentiment Corpus (MVSC), which comprises 3000 English microblog posts related the movie domain. Three independent annotators manually labelled MVSC, following a broad annotation schema about different aspects that can be grasped from natural language text coming from social networks. The contribution is therefore a corpus that comprises five different views for each message, i.e. subjective/objective, sentiment polarity, implicit/explicit, irony, emotion. In order to allow a more detailed investigation on the human labelling behaviour, we provide the annotations of each human annotator involved. |
Tasks | Emotion Recognition, Opinion Mining, Sentiment Analysis |
Published | 2017-04-01 |
URL | https://www.aclweb.org/anthology/E17-1026/ |
https://www.aclweb.org/anthology/E17-1026 | |
PWC | https://paperswithcode.com/paper/a-multi-view-sentiment-corpus |
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An NLP Analysis of Exaggerated Claims in Science News
Title | An NLP Analysis of Exaggerated Claims in Science News |
Authors | Yingya Li, Jieke Zhang, Bei Yu |
Abstract | The discrepancy between science and media has been affecting the effectiveness of science communication. Original findings from science publications may be distorted with altered claim strength when reported to the public, causing misinformation spread. This study conducts an NLP analysis of exaggerated claims in science news, and then constructed prediction models for identifying claim strength levels in science reporting. The results demonstrate different writing styles journal articles and news/press releases use for reporting scientific findings. Preliminary prediction models reached promising result with room for further improvement. |
Tasks | Text Classification |
Published | 2017-09-01 |
URL | https://www.aclweb.org/anthology/W17-4219/ |
https://www.aclweb.org/anthology/W17-4219 | |
PWC | https://paperswithcode.com/paper/an-nlp-analysis-of-exaggerated-claims-in |
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Plotting Markson’s ``Mistress’’
Title | Plotting Markson’s ``Mistress’’ | |
Authors | Conor Kelleher, Mark Keane |
Abstract | The post-modern novel {``}Wittgenstein{'}s Mistress{''} by David Markson (1988) presents the reader with a very challenging non-linear narrative, that itself appears to one of the novel{'}s themes. We present a distant reading of this work designed to complement a close reading of it by David Foster Wallace (1990). Using a combination of text analysis, entity recognition and networks, we plot repetitive structures in the novel{'}s narrative relating them to its critical analysis. | |
Tasks | |
Published | 2017-08-01 |
URL | https://www.aclweb.org/anthology/W17-2205/ |
https://www.aclweb.org/anthology/W17-2205 | |
PWC | https://paperswithcode.com/paper/plotting-marksons-mistress |
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Extracting word lists for domain-specific implicit opinions from corpora
Title | Extracting word lists for domain-specific implicit opinions from corpora |
Authors | N{'u}ria Bertomeu Castell{'o}, Manfred Stede |
Abstract | |
Tasks | Sentiment Analysis |
Published | 2017-01-01 |
URL | https://www.aclweb.org/anthology/W17-6802/ |
https://www.aclweb.org/anthology/W17-6802 | |
PWC | https://paperswithcode.com/paper/extracting-word-lists-for-domain-specific |
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