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1
Addressing Issues of Cross-Linguality in Open-Retrieval Question Answering Systems For Emergent Domains ...
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2
Imagination-Augmented Natural Language Understanding ...
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3
A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Space ...
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4
Question Answering over Text and Tables ...
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5
Investigating Memorization of Conspiracy Theories in Text Generation ...
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6
Neural Stylistic Response Generation with Disentangled Latent Variables ...
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7
Modeling Disclosive Transparency in NLP Application Descriptions ...
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8
A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Space ...
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9
Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering ...
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10
Evaluating Transformer-Based Multilingual Text Classification ...
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11
Cross-Lingual Vision-Language Navigation ...
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12
TabFact: A Large-scale Dataset for Table-based Fact Verification ...
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13
Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization ...
Li, Siyao; Lei, Deren; Qin, Pengda. - : arXiv, 2019
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14
Analyzing and Interpreting Convolutional Neural Networks in NLP ...
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15
Simple Models for Word Formation in English Slang ...
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16
Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media ...
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17
"Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection ...
Wang, William Yang. - : arXiv, 2017
Abstract: Automatic fake news detection is a challenging problem in deception detection, and it has tremendous real-world political and social impacts. However, statistical approaches to combating fake news has been dramatically limited by the lack of labeled benchmark datasets. In this paper, we present liar: a new, publicly available dataset for fake news detection. We collected a decade-long, 12.8K manually labeled short statements in various contexts from PolitiFact.com, which provides detailed analysis report and links to source documents for each case. This dataset can be used for fact-checking research as well. Notably, this new dataset is an order of magnitude larger than previously largest public fake news datasets of similar type. Empirically, we investigate automatic fake news detection based on surface-level linguistic patterns. We have designed a novel, hybrid convolutional neural network to integrate meta-data with text. We show that this hybrid approach can improve a text-only deep learning model. ... : ACL 2017 ...
Keyword: Computation and Language cs.CL; Computers and Society cs.CY; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1705.00648
https://arxiv.org/abs/1705.00648
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18
TFW, DamnGina, Juvie, and Hotsie-Totsie: On the Linguistic and Social Aspects of Internet Slang ...
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19
Automatic detection of speaker state: Lexical, prosodic, and phonetic approaches to level-of-interest and intoxication classification
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 27 (2013) 1, 168-189
OLC Linguistik
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20
“Love ya, jerkface”: using Sparse Log-Linear Models to Build Positive (and Impolite) Relationships with Teens ...
Wang, William Yang; Finkelstein, Samantha; Ogan, Amy. - : Carnegie Mellon University, 2012
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