Neurocomputational models of language processing

JT Hale, L Campanelli, J Li, S Bhattasali… - Annual Review of …, 2022 - annualreviews.org
Efforts to understand the brain bases of language face the Mapping Problem: At what level
do linguistic computations and representations connect to human neurobiology? We review …

ROSE: A neurocomputational architecture for syntax

E Murphy - Journal of Neurolinguistics, 2024 - Elsevier
A comprehensive neural model of language must accommodate four components:
representations, operations, structures and encoding. Recent intracranial research has …

Robust effects of working memory demand during naturalistic language comprehension in language-selective cortex

C Shain, IA Blank, E Fedorenko, E Gibson… - Journal of …, 2022 - Soc Neuroscience
To understand language, we must infer structured meanings from real-time auditory or visual
signals. Researchers have long focused on word-by-word structure building in working …

Le Petit Prince multilingual naturalistic fMRI corpus

J Li, S Bhattasali, S Zhang, B Franzluebbers, WM Luh… - Scientific data, 2022 - nature.com
Neuroimaging using more ecologically valid stimuli such as audiobooks has advanced our
understanding of natural language comprehension in the brain. However, prior naturalistic …

Diverging neural dynamics for syntactic structure building in naturalistic speaking and listening

L Giglio, M Ostarek, D Sharoh… - Proceedings of the …, 2024 - National Acad Sciences
The neural correlates of sentence production are typically studied using task paradigms that
differ considerably from the experience of speaking outside of an experimental setting. In …

Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments

R Ueda, T Taniguchi - arXiv preprint arXiv:2311.04453, 2023 - arxiv.org
As a sub-discipline of evolutionary and computational linguistics, emergent communication
(EC) studies communication protocols, called emergent languages, arising in simulations …

Localizing syntactic composition with left-corner recurrent neural network grammars

Y Sugimoto, R Yoshida, H Jeong, M Koizumi… - Neurobiology of …, 2024 - direct.mit.edu
In computational neurolinguistics, it has been demonstrated that hierarchical models such
as recurrent neural network grammars (RNNGs), which jointly generate word sequences …

Connecting neural response measurements & computational models of language: a non-comprehensive guide

M Abdou - arXiv preprint arXiv:2203.05300, 2022 - arxiv.org
Understanding the neural basis of language comprehension in the brain has been a long-
standing goal of various scientific research programs. Recent advances in language …

On the challenges of fully incremental neural dependency parsing

A Ezquerro, C Gómez-Rodríguez, D Vilares - arXiv preprint arXiv …, 2023 - arxiv.org
Since the popularization of BiLSTMs and Transformer-based bidirectional encoders, state-of-
the-art syntactic parsers have lacked incrementality, requiring access to the whole sentence …

Categorial grammar induction from raw data

C Clark, W Schuler - Findings of the Association for …, 2023 - aclanthology.org
Grammar induction, the task of learning a set of grammatical rules from raw or minimally
labeled text data, can provide clues about what kinds of syntactic structures are learnable …