Papers with feature removal

1 papers
Speech language models lack important brain-relevant semantics (2024.acl-long)

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Challenge: Recent work shows that text-based language models predict both text- and speech-evoked brain activity.
Approach: They remove low-level stimulus features from language models to assess their impact on alignment with fMRI brain recordings during reading and listening.
Outcome: The proposed model removes low-level features from fMRI brain recordings to assess their impact on alignment with fmr recordings.

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