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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.1
- 수록면
- 15 - 52 (38page)
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In this paper, our focus is the connection and influence of language technologies on the research in neurolinguistics. We present a review of brain imaging-based neurolinguistic studies with a focus on the natural language representations, such as word embeddings and pre-trained language models. Mutual enrichment of neurolinguistics and language technologies leads to development of brain-aware natural language representations. The importance of this research area is emphasized by medical applications
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참고문헌 (79)
참고문헌 신청
Abnar, S. / 2018 / Experiential, distributional and dependency-based word embeddings have complementary roles in decoding brain activity / Proceedings of the 8th Workshop on Cognitive Modeling and Computational Linguistics(CMCL 2018) :57~66
Abnar, S. / 2019 / Blackbox Meets Blackbox : Representational Similarity & Stability Analysis of Neural Language Models and Brains / Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP :191~203
Bartunov, Sergey / 2016 / Breaking sticks and ambiguities with adaptive skip-gram / Artificial Intelligence and Statistics :130~138
Bartusiak, Roman / 2019 / WordNet2Vec: Corpora agnostic word vectorization method / Neurocomputing 326:141~150
Bojanowski, Piotr / 2017 / Enriching word vectors with subword information / Transactions of the Association for Computational Linguistics 5:135~146
Abnar, S. / 2019 / Blackbox Meets Blackbox : Representational Similarity & Stability Analysis of Neural Language Models and Brains / Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP :191~203
Bartunov, Sergey / 2016 / Breaking sticks and ambiguities with adaptive skip-gram / Artificial Intelligence and Statistics :130~138
Bartusiak, Roman / 2019 / WordNet2Vec: Corpora agnostic word vectorization method / Neurocomputing 326:141~150
Bojanowski, Piotr / 2017 / Enriching word vectors with subword information / Transactions of the Association for Computational Linguistics 5:135~146
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