Understanding language-elicited EEG data by predicting it from a fine-tuned language model (N19-1)
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| Challenge: | Existing studies have only found two of the ERPs to be predictable from embeddings of a stream of language. |
| Approach: | They propose to fine tune a language model to predict ERPs by embedding a stream of language into a model that allows them to be more accurate. |
| Outcome: | The proposed model fine tunes the ERPs to predict them for the first time. |
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