Why do large language models align with human brains: insights, opportunities, and challenges
Mariya Toneva
Max Planck Institute for Software Systems
07 Jun 2023, 12:15 pm - 1:15 pm
Saarbrücken building E1 5, room 002
Joint Lecture Series
Language models that have been trained to predict the next word over billions
of text documents have been shown to also significantly predict brain
recordings of people comprehending language. Understanding the reasons behind
the observed similarities between language in machines and language in the
brain can lead to more insight into both systems. In this talk, we will discuss
a series of recent works that make progress towards this question along
different dimensions. The unifying principle among these works that allows us
to make scientific claims about why one black box (language model) aligns with
another black box (the human brain) is our ability to make specific
perturbations in the language model and observe their effect on the alignment
with the brain. ...
Language models that have been trained to predict the next word over billions
of text documents have been shown to also significantly predict brain
recordings of people comprehending language. Understanding the reasons behind
the observed similarities between language in machines and language in the
brain can lead to more insight into both systems. In this talk, we will discuss
a series of recent works that make progress towards this question along
different dimensions. The unifying principle among these works that allows us
to make scientific claims about why one black box (language model) aligns with
another black box (the human brain) is our ability to make specific
perturbations in the language model and observe their effect on the alignment
with the brain. Building on this approach, these works reveal that the observed
alignment is due to more than next-word prediction and word-level semantics and
is partially related to joint processing of select linguistic information in
both systems. Furthermore, we find that the brain alignment can be improved by
training a language model to summarize narratives. Taken together, these works
make progress towards determining the sufficient and necessary conditions under
which language in machines aligns with language in the brain.
Read more