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检索条件"机构=Ubiquitous Knowledge Processing Lab Department of Computer Science"
64 条 记 录,以下是21-30 订阅
排序:
Ranking creative language characteristics in small data scenarios
arXiv
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arXiv 2020年
作者: Siekiera, Julia Köppel, Marius Simpson, Edwin Stowe, Kevin Gurevych, Iryna Kramer, Stefan Dept. of Computer Science Johannes Gutenberg-Universitat Mainz Germany Institute for Nuclear Physics Johannes Gutenberg-Universität Mainz Germany Dept. of Computer Science University of Bristol United Kingdom Ubiquitous Knowledge Processing Lab Technische Universität Darmstadt Germany
The ability to rank creative natural language provides an important general tool for downstream language understanding and generation. However, current deep ranking models require substantial amounts of labeled data t... 详细信息
来源: 评论
Fine-tuned neural models for Propaganda Detection at the sentence and fragment levels
arXiv
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arXiv 2019年
作者: Alhindi, Tariq Pfeiffer, Jonas Muresan, Smaranda Department of Computer Science Columbia University Data Science Institute Columbia University Ubiquitous Knowledge Processing Lab Technische Universitat Darmstadt
This paper presents the CUNLP submission for the NLP4IF 2019 shared-task on Fine-Grained Propaganda Detection. Our system finished 5th out of 26 teams on the sentence-level classification task and 5th out of 11 teams ... 详细信息
来源: 评论
Does my rebuttal matter? Insights from a major NLP conference
arXiv
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arXiv 2019年
作者: Gao, Yang Eger, Steffen Kuznetsov, Ilia Gurevych, Iryna Miyao, Yusuke Ubiquitous Knowledge Processing Lab Department of Computer Science Technische Universität Darmstadt Department of Computer Science Graduate School of Information Science and Technology University of Tokyo
Peer review is a core element of the scientific process, particularly in conference-centered fields such as ML and NLP. However, only few studies have evaluated its properties empirically. Aiming to fill this gap, we ... 详细信息
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Revisiting joint modeling of cross-document entity and event coreference resolution
arXiv
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arXiv 2019年
作者: Barhom, Shany Shwartz, Vered Eirew, Alon Bugert, Michael Reimers, Nils Dagan, Ido Computer Science Department Bar-Ilan University Intel AI Lab Israel Ubiquitous Knowledge Processing Lab Technische Universitat Darmstadt Germany
Recognizing coreferring events and entities across multiple texts is crucial for many NLP applications. Despite the task's importance, research focus was given mostly to withindocument entity coreference, with rat...
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Better rewards yield better summaries: Learning to summarise without references
arXiv
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arXiv 2019年
作者: Böhm, Florian Gao, Yang Meyer, Christian M. Shapira, Ori Dagan, Ido Gurevych, Iryna Ubiquitous Knowledge Processing Lab Technische Universität Darmstadt Germany Computer Science Department Bar-Ilan University Ramat-Gan Israel Dept. of Computer Science Royal Holloway University of London
Reinforcement Learning (RL) based document summarisation systems yield state-of-the-art performance in terms of ROUGE scores, because they directly use ROUGE as the rewards during training. However, summaries with hig... 详细信息
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A Bayesian Approach for Sequence Tagging with Crowds
arXiv
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arXiv 2018年
作者: Simpson, Edwin Gurevych, Iryna Department of Computer Science Ubiquitous Knowledge Processing Lab Technische Universität Darmstadt
Current methods for sequence tagging, a core task in NLP, are data hungry, which motivates the use of crowdsourcing as a cheap way to obtain labelled data. However, annotators are often unreliable and current aggregat... 详细信息
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How to Best Predict the Daily Number of New Infections of Covid-19
arXiv
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arXiv 2020年
作者: Skiera, Bernd Jürgensmeier, Lukas Stowe, Kevin Gurevych, Iryna Board of EFL Data Science Institute Goethe University Frankfurt Theodor-W.-Adorno-Platz 4 Frankfurt60629 Germany Deakin University Australia Graduate School of Economics Finance and Management Goethe University Frankfurt Frankfurt60629 Germany Ubiquitous Processing Lab Computer Science Department Technical University of Darmstadt Hochschulstrasse 10 Darmstadt64289 Germany
knowledge about the daily number of new infections of Covid-19 is important because it is the basis for political decisions resulting in lockdowns and urgent health care measures. We use Germany as an example to illus...
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A tool for extracting sense-disambiguated example sentences through user feedback  15
A tool for extracting sense-disambiguated example sentences ...
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Software Demonstrations at the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017
作者: Boullosa, Beto De Castilho, Richard Eckart Geyken, Alexander Lemnitzer, Lothar Gurevych, Iryna Ubiquitous Knowledge Processing Lab Department of Computer Science Technische Universität Darmstadt Germany Berlin-Brandenburg Academy of Sciences Germany
This paper describes an application system aimed to help lexicographers in the extraction of example sentences for a given headword based on its different senses. The tool uses classification and clustering methods an...
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Corrigendum to Unsupervised Latent Dirichlet Allocation for supervised question classification. [Information processing & Management, 54(3), 380-393]
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Information processing & Management 2019年 第3期56卷 1080-1080页
作者: Saeedeh Momtazi Iryna Gurevych Department of Computer Engineering and Information Technology Amirkabir University of Technology Tehran Iran Ubiquitous Knowledge Processing (UKP) Lab TU Darmstadt
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Assessing SRL frameworks with automatic training data expansion  11
Assessing SRL frameworks with automatic training data expans...
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11th Linguistic Annotation Workshop, LAW 2017
作者: Hartmann, Silvana Mújdricza-Maydt, E. Éva Kuznetsov, Ilia Gurevych, Iryna Frank, Anette Ubiquitous Knowledge Processing Lab Department of Computer Science Technische Universität Darmstadt Germany Research Training School AIPHES Department of Computational Linguistics Heidelberg University Germany
We present the first experiment-based study that explicitly contrasts the three major semantic role labeling frameworks. As a prerequisite, we create a dataset labeled with parallel FrameNet-, PropBank-, and VerbNet-s... 详细信息
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