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1
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset ...
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2
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset ...
Zhang, Qiyuan; Wang, Lei; Yu, Sicheng. - : arXiv, 2021
BASE
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3
Investigating Math Word Problems using Pretrained Multilingual Language Models ...
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4
Modeling Transitions of Focal Entities for Conversational Knowledge Base Question Answering ...
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5
Translate and label! An encoder-decoder approach for cross-lingual semantic role labeling
Daza, Angel [Verfasser]; Frank, Anette [Verfasser]; Inui, Kentaro [Herausgeber]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2019
DNB Subject Category Language
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6
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning ...
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7
Cross-lingual semantic specialization via lexical relation induction
Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019
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8
Do we really need fully unsupervised cross-lingual embeddings?
Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : Association for Computational Linguistics, 2019
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9
Neural control of rising and falling tones in Mandarin speakers who stutter
In: Brain & language. - Orlando, Fla. [u.a.] : Elsevier 123 (2012) 3, 211-221
BLLDB
OLC Linguistik
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10
Neural Synchronization during Face-to-Face Communication
Jiang, Jing; Dai, Bohan; Peng, Danling; Zhu, Chaozhe; Liu, Li; Lu, Chunming. - : Society for Neuroscience, 2012
Abstract: Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-face dialog between partners but none during a back-to-back dialog, a face-to-face monologue, or a back-to-back monologue. Moreover, the neural synchronization between partners during the face-to-face dialog resulted primarily from the direct interactions between the partners, including multimodal sensory information integration and turn-taking behavior. The communicating behavior during the face-to-face dialog could be predicted accurately based on the neural synchronization level. These results suggest that face-to-face communication, particularly dialog, has special neural features that other types of communication do not have and that the neural synchronization between partners may underlie successful face-to-face communication.
Keyword: Brief Communications
URL: https://doi.org/10.1523/JNEUROSCI.2926-12.2012
http://www.ncbi.nlm.nih.gov/pubmed/23136442
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6621612/
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11
Generating templates of entity summaries with an entity-aspect model and pattern mining
In: Association for Computational Linguistics. Proceedings of the conference. - Stroudsburg, Penn. : ACL 48 (2010) 1, 640-649
BLLDB
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12
UDEL/SMU at TREC 2009 Entity Track
In: DTIC (2009)
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13
An empirical study of tokenization strategies for biomedical information retrieval
In: Information Retrieval Journal. - Dordrecht [u.a.] : Springer Science + Business Media B.V. 10 (2007) 4-5, 341-363
BLLDB
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14
Diagnostic precision of tumor markers for malignant pleural effusion: a meta-analysis
Liang, Qiu-Li; Shi, Huan-Zhong; Qin, Xue-Jun. - : BMJ Publishing Group Ltd, 2007
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15
Racial mimesis: Translation, literature, and self -fashioning in modern China.
Jiang, Jing. - 2006
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16
An Empirical Study of Tokenization Strategies for Biomedical Information Retrieval
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