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22대 대한민국 국회 국회정보길라잡이 국회의원검색
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This paper explores the intricate dynamics of cross-linguistic transfer in second language acquisition (SLA) research, investigating how the linguistic structure of a native language influences the acquisition of a second language. The study employs transfer learning as a methodology, using the Transformer-based language model, BabyRoberta. The model undergoes pre-training on Korean as the first language (L1) and subsequent fine-tuning with English as the second language (L2). Evaluation involves the BLiMP test suite, a benchmark for assessing syntactic abilities in neural language models. The primary focus is on unraveling transfer effects originating from the native language’s linguistic structure. By examining the model’s performance on syntactic tasks, particularly in the context of English, the research aims to provide insights into how neural language models encode abstract syntactic structures, incorporating inductive biases acquired during pre-training on Korean. This approach not only contributes to the understanding of cross-linguistic influences in SLA but also tries figure interplay between native and second languages within neural language models.

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중세영어 이중모음의 목록 변화 = The inventory changes of diphthongs in Middle English 문안나 p. 1-23

(An) fMRI Study of L2 processing of Korean scrambling by native English speakers Haeil Park p. 25-43

Investigating the link among LMA, FLLA, and listening comprehension of Chinese EFL learners Jing Sun, Dong-Jin Shin p. 45-68

Investigating syntactic interference effects in neural language models for second language acquisition Keonwoo Koo, Jaemin Lee, Myung-Kwan Park p. 69-88

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권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
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