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1
Entity-Enriched Neural Models for Clinical Question Answering
In: arXiv (2021)
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2
Speakers Enhance Contextually Confusable Words
Meinhardt, Eric; Bakovic, Eric; Bergen, Leon. - : eScholarship, University of California, 2020
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3
An empirical investigation of neural methods for content scoring of science explanations
Riordan, Brian; Bichler, Sarah; Bradford, Allison. - : eScholarship, University of California, 2020
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4
Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations ...
Coope, Sam; Farghly, Tyler; Gerz, Daniela. - : Apollo - University of Cambridge Repository, 2020
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5
Efficient Intent Detection with Dual Sentence Encoders ...
Casanueva, Inigo; Temcinas, Tadas; Gerz, Daniela. - : Apollo - University of Cambridge Repository, 2020
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6
Complementary Systems for Off-Topic Spoken Response Detection ...
Raina, Vatsal; Gales, Mark; Knill, Katherine. - : Apollo - University of Cambridge Repository, 2020
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7
Multidirectional Associative Optimization of Function-Specific Word Representations ...
Gerz, Daniela; Vulic, Ivan; Rei, Marek. - : Apollo - University of Cambridge Repository, 2020
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8
Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter ...
Conforti, Costanza; Berndt, Jakob; Pilehvar, Mohammad Taher. - : Apollo - University of Cambridge Repository, 2020
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9
Investigating the Effect of Auxiliary Objectives for the Automated Grading of Learner English Speech Transcriptions ...
Craighead, Hannah; Caines, Andrew; Buttery, Paula. - : Apollo - University of Cambridge Repository, 2020
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10
Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces ...
Vulic, Ivan; Korhonen, Anna; Glavas, Goran. - : Apollo - University of Cambridge Repository, 2020
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11
Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces
Vulic, Ivan; Korhonen, Anna; Glavas, Goran. - : 5TH WORKSHOP ON REPRESENTATION LEARNING FOR NLP (REPL4NLP-2020), 2020
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12
Investigating the Effect of Auxiliary Objectives for the Automated Grading of Learner English Speech Transcriptions
Yannakoudakis, Helen; Craighead, Hannah; Caines, Andrew. - : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020
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13
Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter
Conforti, Costanza; Berndt, Jakob; Pilehvar, Mohammad Taher. - : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020
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14
Complementary Systems for Off-Topic Spoken Response Detection
Raina, Vatsal; Gales, Mark; Knill, Katherine; Linguist, Assoc Computat. - : Association for Computational Linguistics, 2020. : https://aclanthology.org/volumes/2020.bea-1/, 2020. : INNOVATIVE USE OF NLP FOR BUILDING EDUCATIONAL APPLICATIONS, 2020
Abstract: Increased demand to learn English for business and education has led to growing interest in automatic spoken language assessment and teaching systems. With this shift to automated approaches it is important that systems reliably assess all aspects of a candidate's responses. This paper examines one form of spoken language assessment; whether the response from the candidate is relevant to the prompt provided. This will be referred to as off-topic spoken response detection. Two forms of previously proposed approaches are examined in this work: the hierarchical attention-based topic model (HATM); and the similarity grid model (SGM). The work focuses on the scenario when the prompt, and associated responses, have not been seen in the training data, enabling the system to be applied to new test scripts without the need to collect data or retrain the model. To improve the performance of the systems for unseen prompts, data augmentation based on easy data augmentation (EDA) and translation based approaches are applied. Additionally for the HATM, a form of prompt dropout is described. The systems were evaluated on both seen and unseen prompts from Linguaskill Business and General English tests. For unseen data the performance of the HATM was improved using data augmentation, in contrast to the SGM where no gains were obtained. The two approaches were found to be complementary to one another, yielding a combined F(0.5) score of 0.814 for off-topic response detection where the prompts have not been seen in training. ; ALTA
URL: https://doi.org/10.17863/CAM.53705
https://www.repository.cam.ac.uk/handle/1810/306619
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15
Multidirectional Associative Optimization of Function-Specific Word Representations
Gerz, Daniela; Vulic, Ivan; Rei, Marek. - : Association for Computational Linguistics, 2020. : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020
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16
Efficient Intent Detection with Dual Sentence Encoders
Casanueva, Inigo; Temcinas, Tadas; Gerz, Daniela. - : NLP FOR CONVERSATIONAL AI, 2020
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17
Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations
Coope, Sam; Farghly, Tyler; Gerz, Daniela. - : Association for Computational Linguistics, 2020. : 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2020), 2020
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18
Tree-Structured Neural Topic Model
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19
GASC: Genre-Aware Semantic Change for Ancient Greek ...
Perrone, Valerio; Palma, Marco; Hengchen, Simon. - : Apollo - University of Cambridge Repository, 2019
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20
GASC: Genre-Aware Semantic Change for Ancient Greek
Perrone, Valerio; Palma, Marco; Hengchen, Simon. - : Association for Computational Linguistics, 2019. : 1ST INTERNATIONAL WORKSHOP ON COMPUTATIONAL APPROACHES TO HISTORICAL LANGUAGE CHANGE, 2019
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