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Greta Tuckute Profile picture
Greta Tuckute
@GretaTuckute
PhD candidate, Brain and Cognitive Sciences MIT. Interested in language in biological brains and artificial ones.
Jul 3, 2024 • 11 tweets • 3 min read
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 New work! Localizing the human language network in ~3.5 minutes using speeded reading.

Co-led with @elizj_lee, and with @aloxatel @ev_fedorenko

Paper:
Code: biorxiv.org/content/10.110…
rb.gy/x2rjzj 2/
 We present a speeded version of a widely used localizer (Fedorenko 2010) for the language network. In brief, the lang. network is a set of interconnected regions in the frontal and temporal lobes, selective for lang. over various non-lang. tasks (see ).rb.gy/g9pnkn
May 2, 2024 • 12 tweets • 4 min read
1/
 Really excited to share:
Language in Brains, Minds, and Machines w @Nancy_Kanwisher @ev_fedorenko
@AnnualReviews

We survey the insights that language models (LMs) provide on the question of how language is represented and processed in the human brain.

rb.gy/8afztv
Image 2/
 First, what are we trying to model 🧠?
We discuss the human language system as a well-defined target for modeling efforts aimed at understanding the representations and computations underlying language (see also e.g., ).
Image
Apr 17, 2023 • 13 tweets • 7 min read
There is much discussion about capabilities of GPT models. But how accurate are such models as models of language processing in the 🧠?

Here, we demonstrate that GPT is accurate enough to noninvasively drive and suppress 🧠activity in the language network of new individuals.

1/ Image "Driving and suppressing the human language network using large language models"
Preprint: tinyurl.com/m4yy5mwf

With an amazing team: @aloxatel @ShashankSrikant @MayaTaliaferro Mingye (Christina) Wang @martin_schrimpf @cvnlab @ev_fedorenko

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Jul 25, 2022 • 10 tweets • 3 min read
PINEAPPLE, LIGHT, HAPPY, AVALANCHE, BURDEN

Some of these words are consistently remembered better than others. Why is that? Here we provide a simple Bayesian account and show that it explains >80% of variance in word memorability psyarxiv.com/p6kv9/ Big joint effort with @kmahowald (co-1st) @phillip_isola @AudeOliva @LanguageMIT @ev_fedorenko
Jul 11, 2022 • 6 tweets • 2 min read
We are excited to present SentSpace at #NAACL2022 on Tuesday (System Demo session, 4.15pm PT, 7th floor)! SentSpace is a tool for characterizing text using diverse lexical, syntactic, and semantic features related to how humans process and understand language. Many fields rely on numerical representations of text. SentSpace is a tool for streamlined evaluation of words, phrases and sentences. SentSpace features are derived from psycholinguistic experiments, large-scale corpora, and theoretically motivated models of language processing.