Paper Group NANR 94
PJAIT Systems for the WMT 2016. TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling. Modelling the Combination of Generic and Target Domain Embeddings in a Convolutional Neural Network for Sentence Classification. Text Segmentation of Digitized Clinical Texts. Extractive Summ …
PJAIT Systems for the WMT 2016
| Title | PJAIT Systems for the WMT 2016 |
| Authors | Krzysztof Wolk, Krzysztof Marasek |
| Abstract | |
| Tasks | Domain Adaptation, Language Modelling, Machine Translation, Transliteration, Word Alignment |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2328/ |
| https://www.aclweb.org/anthology/W16-2328 | |
| PWC | https://paperswithcode.com/paper/pjait-systems-for-the-wmt-2016 |
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TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling
| Title | TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling |
| Authors | Alex Panchenko, er, Stefano Faralli, Eugen Ruppert, Steffen Remus, Hubert Naets, C{'e}drick Fairon, Simone Paolo Ponzetto, Chris Biemann |
| Abstract | |
| Tasks | Language Modelling |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1206/ |
| https://www.aclweb.org/anthology/S16-1206 | |
| PWC | https://paperswithcode.com/paper/taxi-at-semeval-2016-task-13-a-taxonomy |
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Modelling the Combination of Generic and Target Domain Embeddings in a Convolutional Neural Network for Sentence Classification
| Title | Modelling the Combination of Generic and Target Domain Embeddings in a Convolutional Neural Network for Sentence Classification |
| Authors | Nut Limsopatham, Nigel Collier |
| Abstract | |
| Tasks | Chunking, Named Entity Recognition, Part-Of-Speech Tagging, Sentence Classification, Text Classification, Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2918/ |
| https://www.aclweb.org/anthology/W16-2918 | |
| PWC | https://paperswithcode.com/paper/modelling-the-combination-of-generic-and |
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Text Segmentation of Digitized Clinical Texts
| Title | Text Segmentation of Digitized Clinical Texts |
| Authors | Cyril Grouin |
| Abstract | In this paper, we present the experiments we made to recover the original page layout structure into two columns from layout damaged digitized files. We designed several CRF-based approaches, either to identify column separator or to classify each token from each line into left or right columns. We achieved our best results with a model trained on homogeneous corpora (only files composed of 2 columns) when classifying each token into left or right columns (overall F-measure of 0.968). Our experiments show it is possible to recover the original layout in columns of digitized documents with results of quality. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1570/ |
| https://www.aclweb.org/anthology/L16-1570 | |
| PWC | https://paperswithcode.com/paper/text-segmentation-of-digitized-clinical-texts |
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Extractive Summarization under Strict Length Constraints
| Title | Extractive Summarization under Strict Length Constraints |
| Authors | Yashar Mehdad, Am Stent, a, Kapil Thadani, Dragomir Radev, Youssef Billawala, Karolina Buchner |
| Abstract | In this paper we report a comparison of various techniques for single-document extractive summarization under strict length budgets, which is a common commercial use case (e.g. summarization of news articles by news aggregators). We show that, evaluated using ROUGE, numerous algorithms from the literature fail to beat a simple lead-based baseline for this task. However, a supervised approach with lightweight and efficient features improves over the lead-based baseline. Additional human evaluation demonstrates that the supervised approach also performs competitively with a commercial system that uses more sophisticated features. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1493/ |
| https://www.aclweb.org/anthology/L16-1493 | |
| PWC | https://paperswithcode.com/paper/extractive-summarization-under-strict-length |
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Building a Dataset for Possessions Identification in Text
| Title | Building a Dataset for Possessions Identification in Text |
| Authors | Carmen Banea, Xi Chen, Rada Mihalcea |
| Abstract | Just as industrialization matured from mass production to customization and personalization, so has the Web migrated from generic content to public disclosures of one{'}s most intimately held thoughts, opinions and beliefs. This relatively new type of data is able to represent finer and more narrowly defined demographic slices. If until now researchers have primarily focused on leveraging personalized content to identify latent information such as gender, nationality, location, or age of the author, this study seeks to establish a structured way of extracting possessions, or items that people own or are entitled to, as a way to ultimately provide insights into people{'}s behaviors and characteristics. In order to promote more research in this area, we are releasing a set of 798 possessions extracted from blog genre, where possessions are marked at different confidence levels, as well as a detailed set of guidelines to help in future annotation studies. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1592/ |
| https://www.aclweb.org/anthology/L16-1592 | |
| PWC | https://paperswithcode.com/paper/building-a-dataset-for-possessions |
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BAD LUC@WMT 2016: a Bilingual Document Alignment Platform Based on Lucene
| Title | BAD LUC@WMT 2016: a Bilingual Document Alignment Platform Based on Lucene |
| Authors | Laurent Jakubina, Phillippe Langlais |
| Abstract | |
| Tasks | Information Retrieval, Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2370/ |
| https://www.aclweb.org/anthology/W16-2370 | |
| PWC | https://paperswithcode.com/paper/bad-lucwmt-2016-a-bilingual-document |
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USFD’s Phrase-level Quality Estimation Systems
| Title | USFD’s Phrase-level Quality Estimation Systems |
| Authors | Varvara Logacheva, Fr{'e}d{'e}ric Blain, Lucia Specia |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2386/ |
| https://www.aclweb.org/anthology/W16-2386 | |
| PWC | https://paperswithcode.com/paper/usfdas-phrase-level-quality-estimation |
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Unbabel’s Participation in the WMT16 Word-Level Translation Quality Estimation Shared Task
| Title | Unbabel’s Participation in the WMT16 Word-Level Translation Quality Estimation Shared Task |
| Authors | Andr{'e} F. T. Martins, Ram{'o}n Astudillo, Chris Hokamp, Fabio Kepler |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2387/ |
| https://www.aclweb.org/anthology/W16-2387 | |
| PWC | https://paperswithcode.com/paper/unbabels-participation-in-the-wmt16-word |
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Recurrent Neural Network based Translation Quality Estimation
| Title | Recurrent Neural Network based Translation Quality Estimation |
| Authors | Hyun Kim, Jong-Hyeok Lee |
| Abstract | |
| Tasks | Language Modelling, Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2384/ |
| https://www.aclweb.org/anthology/W16-2384 | |
| PWC | https://paperswithcode.com/paper/recurrent-neural-network-based-translation |
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SimpleNets: Quality Estimation with Resource-Light Neural Networks
| Title | SimpleNets: Quality Estimation with Resource-Light Neural Networks |
| Authors | Gustavo Paetzold, Lucia Specia |
| Abstract | |
| Tasks | Machine Translation, Text Simplification, Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2388/ |
| https://www.aclweb.org/anthology/W16-2388 | |
| PWC | https://paperswithcode.com/paper/simplenets-quality-estimation-with-resource |
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Newtonian Scene Understanding: Unfolding the Dynamics of Objects in Static Images
| Title | Newtonian Scene Understanding: Unfolding the Dynamics of Objects in Static Images |
| Authors | Roozbeh Mottaghi, Hessam Bagherinezhad, Mohammad Rastegari, Ali Farhadi |
| Abstract | In this paper, we study the challenging problem of predicting the dynamics of objects in static images. Given a query object in an image, our goal is to provide a physical understanding of the object in terms of the forces acting upon it and its long term motion as response to those forces. Direct and explicit estimation of the forces and the motion of objects from a single image is extremely challenging. We define intermediate physical abstractions called Newtonian scenarios and introduce Newtonian Neural Network (N^3) that learns to map a single image to a state in a Newtonian scenario. Our experimental evaluations show that our method can reliably predict dynamics of a query object from a single image. In addition, our approach can provide physical reasoning that supports the predicted dynamics in terms of velocity and force vectors. To spur research in this direction we compiled Visual Newtonian Dynamics (VIND) dataset that includes more than 6000 videos aligned with Newtonian scenarios represented using game engines, and more than 4500 still images with their ground truth dynamics. |
| Tasks | Scene Understanding |
| Published | 2016-06-01 |
| URL | http://openaccess.thecvf.com/content_cvpr_2016/html/Mottaghi_Newtonian_Scene_Understanding_CVPR_2016_paper.html |
| http://openaccess.thecvf.com/content_cvpr_2016/papers/Mottaghi_Newtonian_Scene_Understanding_CVPR_2016_paper.pdf | |
| PWC | https://paperswithcode.com/paper/newtonian-scene-understanding-unfolding-the |
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Stochastic Three-Composite Convex Minimization
| Title | Stochastic Three-Composite Convex Minimization |
| Authors | Alp Yurtsever, Bang Cong Vu, Volkan Cevher |
| Abstract | We propose a stochastic optimization method for the minimization of the sum of three convex functions, one of which has Lipschitz continuous gradient as well as restricted strong convexity. Our approach is most suitable in the setting where it is computationally advantageous to process smooth term in the decomposition with its stochastic gradient estimate and the other two functions separately with their proximal operators, such as doubly regularized empirical risk minimization problems. We prove the convergence characterization of the proposed algorithm in expectation under the standard assumptions for the stochastic gradient estimate of the smooth term. Our method operates in the primal space and can be considered as a stochastic extension of the three-operator splitting method. Finally, numerical evidence supports the effectiveness of our method in real-world problems. |
| Tasks | Stochastic Optimization |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6127-stochastic-three-composite-convex-minimization |
| http://papers.nips.cc/paper/6127-stochastic-three-composite-convex-minimization.pdf | |
| PWC | https://paperswithcode.com/paper/stochastic-three-composite-convex |
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Proceedings of the Australasian Language Technology Association Workshop 2016
| Title | Proceedings of the Australasian Language Technology Association Workshop 2016 |
| Authors | |
| Abstract | |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/U16-1000/ |
| https://www.aclweb.org/anthology/U16-1000 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-australasian-language |
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| Framework | |
Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)
| Title | Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT) |
| Authors | |
| Abstract | |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-3900/ |
| https://www.aclweb.org/anthology/W16-3900 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-2nd-workshop-on-noisy-user |
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