Papers by Itsuki Okimura

1 papers
On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific Neurons (2024.naacl-long)

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Challenge: Existing decoder-based pre-trained language models demonstrate excellent multilingual capabilities, but it is unclear how they handle multilingualism.
Approach: They propose to examine the neuron-level internal behavior of decoder-based PLMs by finding neurons that fire “uniquely for each language” within decoded PLM models.
Outcome: The proposed models fire “uniquely for each language” and show that language-specific neurons are unique, with a slight overlap (5%) between languages.

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