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Problematizing Fluent Speakers’ Unintentional Exclusion of Emergent Bilinguals: A Case Study of an English-Medium Instruction Classroom in Japan
In: International Journal of Literacy, Culture, and Language Education; Vol. 2 (2022): Special Issue: Language Weaponization in Society and Education; 6-19 ; 2642-4002 (2022)
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2
Developing Critical Cultural Awareness in the ELT Classroom
In: Faculty Publications: Department of Teaching, Learning and Teacher Education (2022)
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3
A quantitative perspective on Japanese accent
In: 34th Paris Meeting on East Asian Linguistics ; https://hal.archives-ouvertes.fr/hal-03283679 ; 34th Paris Meeting on East Asian Linguistics, Jul 2021, Paris, France (2021)
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4
Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
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5
Embracing Ambiguity: Shifting the Training Target of NLI Models ...
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6
Improving Multilingual Translation by Representation and Gradient Regularization ...
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7
Effect of Visual Extensions on Natural Language Understanding in Vision-and-Language Models ...
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8
Embracing Ambiguity: Shifting the Training Target of NLI Models ...
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9
Improving the Robustness of QA Models to Challenge Sets with Variational Question-Answer Pair Generation ...
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10
Maintaining Common Ground in Dynamic Environments ...
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11
Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical Overlap ...
Abstract: Question answering (QA) models for reading comprehension have been demonstrated to exploit unintended dataset biases such as question-context lexical overlap. This hinders QA models from generalizing to under-represented samples such as questions with low lexical overlap. Question generation (QG), a method for augmenting QA datasets, can be a solution for such performance degradation if QG can properly debias QA datasets. However, we discover that recent neural QG models are biased towards generating questions with high lexical overlap, which can amplify the dataset bias. Moreover, our analysis reveals that data augmentation with these QG models frequently impairs the performance on questions with low lexical overlap, while improving that on questions with high lexical overlap. To address this problem, we use a synonym replacement-based approach to augment questions with low lexical overlap. We demonstrate that the proposed data augmentation approach is simple yet effective to mitigate the degradation ... : MRQA workshop at EMNLP 2021 ...
Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2109.11256
https://arxiv.org/abs/2109.11256
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12
The Effect of Phonological Short-Term Memory on Japanese EFL Learners’ Listening Skills
KONDO, Akiko. - : 兵庫教育大学, 2021
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13
Bend Like Bamboo: Resilience and Tools for Teaching in an Unstable World
In: South East Coastal Conference on Languages & Literatures (SECCLL) (2021)
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14
A quantitative perspective on Japanese accent
In: 34th Paris Meeting on East Asian Linguistics ; https://hal.archives-ouvertes.fr/hal-03283679 ; 34th Paris Meeting on East Asian Linguistics, Jul 2021, Paris, France (2021)
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15
Effects of gender on language revitalisation & documentation in the Ryukyus
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16
Multilingual society:the legacy of the Tokyo Olympics and Paralympics?
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17
Maintaining Common Ground in Dynamic Environments
In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 995-1011 (2021) (2021)
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18
An Evaluation Dataset for Identifying Communicative Functions of Sentences in English Scholarly Papers
In: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) ; 12th Conference on Language Resources and Evaluation (LREC 2020) ; https://hal.archives-ouvertes.fr/hal-03272825 ; 12th Conference on Language Resources and Evaluation (LREC 2020), May 2020, Marseille, France (2020)
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19
Keyphrase Generation for Scientific Document Retrieval
In: The 58th Annual Meeting of the Association for Computational Linguistics (ACL) ; https://hal.archives-ouvertes.fr/hal-02556086 ; The 58th Annual Meeting of the Association for Computational Linguistics (ACL), Jul 2020, Online, United States. ⟨10.18653/v1/2020.acl-main.105⟩ (2020)
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20
非漢字系初級学習者の読解困難点 [Difficultés de lecture en japonais chez les apprenants du niveau débutant issus de culture alphabétique]
In: 日本語学習者の読解過程の解明 [Analyses du processus de lecture des apprenants de japonais] ; https://halshs.archives-ouvertes.fr/halshs-02415261 ; 日本語学習者の読解過程の解明 [Analyses du processus de lecture des apprenants de japonais], Coco shuppan, 2020 (2020)
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