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1
Substructure Substitution: Structured Data Augmentation for NLP ...
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2
On Generalization in Coreference Resolution ...
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3
Exemplar-Controllable Paraphrasing and Translation using Bitext ...
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4
Deep Clustering of Text Representations for Supervision-free Probing of Syntax ...
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5
Mining Knowledge for Natural Language Inference from Wikipedia Categories ...
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6
Beyond BLEU: Training Neural Machine Translation with Semantic Similarity ...
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7
Understanding stories via event sequence modeling
Peng, Haoruo. - 2018
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8
Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext ...
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9
A Study of All-Convolutional Encoders for Connectionist Temporal Classification ...
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10
Parsing Speech: A Neural Approach to Integrating Lexical and Acoustic-Prosodic Information ...
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11
Efficient Segmental Cascades for Speech Recognition ...
Tang, Hao; Wang, Weiran; Gimpel, Kevin. - : arXiv, 2016
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12
Discriminative Segmental Cascades for Feature-Rich Phone Recognition ...
Tang, Hao; Wang, Weiran; Gimpel, Kevin. - : arXiv, 2015
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13
Phrase Dependency Machine Translation with Quasi-Synchronous Tree-to-Tree Features ...
Gimpel, Kevin; Smith, Noah A.. - : Carnegie Mellon University, 2014
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14
Phrase Dependency Machine Translation with Quasi-Synchronous Tree-to-Tree Features ...
Gimpel, Kevin; Smith, Noah A.. - : Carnegie Mellon University, 2014
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15
Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters ...
Olutobi Owoputi; O'Connor, Brendan; Dyer, Chris. - : Carnegie Mellon University, 2013
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16
Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters ...
Abstract: We consider the problem of part-of-speech tagging for informal, online conversational text. We systematically evaluate the use of large-scale unsupervised word clustering and new lexical features to improve tagging accuracy. With these features, our system achieves state-of-the-art tagging results on both Twitter and IRC POS tagging tasks; Twitter tagging is improved from 90% to 93% accuracy (more than 3% absolute). Qualitative analysis of these word clusters yields insights about NLP and linguistic phenomena in this genre. Additionally, we contribute the first POS annotation guidelines for such text and release a new dataset of English language tweets annotated using these guidelines. Tagging software, annotation guidelines, and large-scale word clusters are available at: http://www.ark.cs.cmu.edu/TweetNLP This paper describes release 0.3 of the “CMU Twitter Part-of-Speech Tagger” and annotated data. ...
Keyword: 89999 Information and Computing Sciences not elsewhere classified; FOS Computer and information sciences
URL: https://dx.doi.org/10.1184/r1/6473408.v1
https://kilthub.cmu.edu/articles/Improved_Part-of-Speech_Tagging_for_Online_Conversational_Text_with_Word_Clusters/6473408/1
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17
Concavity and Initialization for Unsupervised Dependency Parsing ...
Gimpel, Kevin; Smith, Noah A.. - : Carnegie Mellon University, 2012
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18
Concavity and Initialization for Unsupervised Dependency Parsing ...
Gimpel, Kevin; Smith, Noah A.. - : Carnegie Mellon University, 2012
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19
Generative Models of Monolingual and Bilingual Gappy Patterns ...
Gimpel, Kevin; Smith, Noah A.. - : Carnegie Mellon University, 2011
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20
Generative Models of Monolingual and Bilingual Gappy Patterns ...
Gimpel, Kevin; Smith, Noah A.. - : Carnegie Mellon University, 2011
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