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This study examines whether sentence-level memory load in comprehension is better explained by linear proximity between syntactically related words or by the structural density of the intervening material. Building on locality-based…

Computation and Language · Computer Science 2025-09-29 Krishna Aggarwal

Language decoding studies have identified word representations which can be used to predict brain activity in response to novel words and sentences (Anderson et al., 2016; Pereira et al., 2018). The unspoken assumption of these studies is…

Computation and Language · Computer Science 2018-06-05 Jon Gauthier , Anna Ivanova

We investigate neural models' ability to capture lexicosyntactic inferences: inferences triggered by the interaction of lexical and syntactic information. We take the task of event factuality prediction as a case study and build a…

Computation and Language · Computer Science 2018-08-21 Aaron Steven White , Rachel Rudinger , Kyle Rawlins , Benjamin Van Durme

In this article we present a multivariate model for determining the different syntactic, semantic, and form (surface-structure) processes underlying the comprehension of simple phrases. This model is applied to EEG signals recorded during a…

Computation and Language · Computer Science 2018-04-17 Sabine Ploux , Viviane Déprez

Recent studies have shown how spiking networks can learn complex functionality through error-correcting plasticity, but the resulting structures and dynamics remain poorly studied. To elucidate how these models may link to observed dynamics…

Neurons and Cognition · Quantitative Biology 2025-08-19 Jonas Oberste-Frielinghaus , Anno C. Kurth , Julian Göltz , Laura Kriener , Junji Ito , Mihai A. Petrovici , Sonja Grün

We describe an "interpretability illusion" that arises when analyzing the BERT model. Activations of individual neurons in the network may spuriously appear to encode a single, simple concept, when in fact they are encoding something far…

Computation and Language · Computer Science 2021-04-16 Tolga Bolukbasi , Adam Pearce , Ann Yuan , Andy Coenen , Emily Reif , Fernanda Viégas , Martin Wattenberg

Deep learning sequence models have led to a marked increase in performance for a range of Natural Language Processing tasks, but it remains an open question whether they are able to induce proper hierarchical generalizations for…

Computation and Language · Computer Science 2019-06-11 Ethan Wilcox , Roger Levy , Richard Futrell

Psychological investigations have led to considerable insight into the working of the human language comprehension system. In this article, we look at a set of principles derived from psychological findings to argue for a particular…

cmp-lg · Computer Science 2008-02-03 Kavi Mahesh , Kurt P. Eiselt

Individual-intelligence research, from a neurological perspective, discusses the hierarchical layers of the cortex as a structure that performs conceptual abstraction and specification. This theory has been used to explain how motor-cortex…

Computers and Society · Computer Science 2007-05-23 Marko A. Rodriguez

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 modelling and in neuroimaging methodology promise potential…

Computation and Language · Computer Science 2022-03-11 Mostafa Abdou

Language exhibits structure at different scales, ranging from subwords to words, sentences, paragraphs, and documents. To what extent do deep models capture information at these scales, and can we force them to better capture structure…

Computation and Language · Computer Science 2020-11-11 Alex Tamkin , Dan Jurafsky , Noah Goodman

We investigate cortical learning from the perspective of mechanism design. First, we show that discretizing standard models of neurons and synaptic plasticity leads to rational agents maximizing simple scoring rules. Second, our main result…

Artificial Intelligence · Computer Science 2014-01-08 David Balduzzi

A longstanding question in cognitive science concerns the learning mechanisms underlying compositionality in human cognition. Humans can infer the structured relationships (e.g., grammatical rules) implicit in their sensory observations…

Machine Learning · Computer Science 2021-05-20 Jacob Russin , Roland Fernandez , Hamid Palangi , Eric Rosen , Nebojsa Jojic , Paul Smolensky , Jianfeng Gao

What is sentence meaning and its ideal representation? Much of the expressive power of human language derives from semantic composition, the mind's ability to represent meaning hierarchically & relationally over constituents. At the same…

Computation and Language · Computer Science 2023-05-29 Rohan Pandey

With the advent of powerful neural language models over the last few years, research attention has increasingly focused on what aspects of language they represent that make them so successful. Several testing methodologies have been…

Computation and Language · Computer Science 2023-05-26 Jordan Kodner , Nitish Gupta

Originally formalized with symbolic representations, syntactic trees may also be effectively represented in the activations of large language models (LLMs). Indeed, a 'Structural Probe' can find a subspace of neural activations, where…

Computation and Language · Computer Science 2024-12-10 Pablo Diego-Simón , Stéphane D'Ascoli , Emmanuel Chemla , Yair Lakretz , Jean-Rémi King

This paper proposes a new approach to Machine Learning (ML) that focuses on unsupervised continuous context-dependent learning of complex patterns. Although the proposal is partly inspired by some of the current knowledge about the…

Neural and Evolutionary Computing · Computer Science 2024-05-07 Valentin Puente Varona

Syntactic structure of sentences in a document substantially informs about its authorial writing style. Sentence representation learning has been widely explored in recent years and it has been shown that it improves the generalization of…

Computation and Language · Computer Science 2022-02-25 Fereshteh Jafariakinabad , Kien A. Hua

The meaning of a natural language utterance is largely determined from its syntax and words. Additionally, there is evidence that humans process an utterance by separating knowledge about the lexicon from syntax knowledge. Theories from…

Computation and Language · Computer Science 2020-02-21 Tristan Thrush

Linear sequences of words are implicitly represented in our brains by hierarchical structures that organize the composition of words in sentences. Linguists formalize different frameworks to model this hierarchy; two of the most common…

Computation and Language · Computer Science 2024-03-18 Omar Momen