Papers with native language learners
On the Nature of BERT: Correlating Fine-Tuning and Linguistic Competence (2022.coling-1)
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| Challenge: | Several studies on the interpretation of Neural Language Models (NLMs) focus on the linguistic generalization abilities of pre-trained models, but little attention is paid to how the linguistic knowledge of the models changes during fine-tuning. |
| Approach: | They propose to examine whether a wide range of linguistic phenomena are forgotten during fine-tuning and whether it is possible to predict the fine- tuned accuracy solely relying on the assessed linguistic competence. |
| Outcome: | The proposed model can predict the evolution of written language competence of native language learners based on the assessed linguistic competence. |