24 papers · ranked by Valyu relevance
Casto, Colton, Ivanova, Anna + 4 more
Language understanding entails not just extracting the surface-level meaning of the linguistic input, but constructing rich mental models of the situation it describes. Here we propose that because processing within the brain's core language system is fundamentally limited, deeply understanding language requires…
Muge Ozker, Atsuko Takashima, Laura Giglio, Florian Hintz + 2 more
Language processing is supported by distributed neural systems. Yet most research examines these systems at the population-average level, obscuring how individual cognitive differences shape language-related brain activity. In this study, we combined comprehensive cognitive assessments and task-based fMRI in a large…
Ruimin Gao, Chandler Cheung, Matthew Siegelman, Alvincé L. A. Pongos + 4 more
A network of left frontal and temporal brain areas supports language comprehension and production, implementing computations related to word retrieval and combinatorial linguistic processing. Here, we ask: are computations over linguistic input driven in a bottom-up way, by the input, or in a top-down way, by task…
Eric Laporte
During the recent years, the use of linguistic data for language processing increased progressively. Such data are now commonly called language resources. Most of the language resources used for this purpose are collections of texts as the Brown Corpus and the Penn Treebank, but electronic lexicons (WordNet, FrameNet…
Tamar I. Regev, Hee So Kim, Niharika Jhingan, Sara Swords + 4 more
Human speech carries information beyond the words themselves: pitch, loudness, duration, and pauses—jointly referred to as ‘prosody’—emphasize critical words, help group words into phrases, and convey emotional and other socially-relevant information. Using a novel fMRI paradigm, we identify a set of prosody-responsive…
Angélica Gutiérrez Cisneros, Alice Foucart, Angèle Brunellière
Over the past 30 years, there has been significant development in the understanding of the brain mechanisms underlying pragmatic processing. The primary purpose of the present review is to delve into the origins of neuropragmatics, defined as the study of the neural basis of pragmatic processing, tracing its…
Jingmin An, Yilong Song, Ruolin Yang, Nai Ding + 6 more
Large Language Models (LLMs) demonstrate human-level or even superior language abilities, effectively modeling syntactic structures, yet the specific computational modules responsible remain unclear. A key question is whether LLM behavioral capabilities stem from mechanisms akin to those in the human brain. To address…
Antonio Moreno, Marie Amalric, Manon Pietrantoni, Séverine Becuwe + 4 more
The ability to compose complex mental representations by recombining simpler primitives is a characteristic of the human brain that manifests itself in a variety of domains such as spoken or written language, mathematics, or social reasoning. While it is known that these domains rest on partially distinct brain…
Ruimin Gao, Chandler Cheung, Matthew Siegelman, Alvincé L. A. Pongos + 4 more
A network of left frontal and temporal brain areas supports language comprehension and production, implementing computations related to word retrieval and combinatorial linguistic processing. Here, we ask: to what extent are responses to language in this language network stable across task contexts, and how does this…
Agata Wolna, Aaron Wright, Colton Casto, Samuel Hutchinson + 2 more
Although language neuroscience has largely focused on “core” left frontal and temporal brain areas and their right-hemisphere homotopes, numerous other areas-cortical and subcortical-have been implicated in linguistic processing. However, these areas' contributions to language remain unclear given that the evidence for…
Thomas Dighiero-Brecht, Naama Friedmann, Luigi Rizzi, Christophe Pallier + 1 more
Although the brain areas for language processing are well delimited, whether lexical-semantic and syntactic processes are spatially segregated remains debated. To clarify this issue, we conducted two experiments using 7-Tesla functional MRI in 20 participants performing: a functional localizer involving reading…
Fudong Zhang, Bo Chai, Yujie Wu, Wai Ting Siok + 1 more
Elucidating the language-brain relationship requires bridging the methodological gap between linguistics’ abstract theoretical frameworks and neuroscience’s empirical neural data. As an interdisciplinary cornerstone, computational neuroscience formalizes language’s hierarchical and dynamic structures into testable…
Nathan Schneider, Antonios Anastasopoulos
This work aims to shine a spotlight on the topic of metalanguage. We first define metalanguage, link it to NLP and LLMs, and then discuss our two labs' metalanguage-centered efforts. Finally, we discuss four dimensions of metalanguage and metalinguistic tasks, offering a list of understudied future research directions.
Francisco J. López
Linguistic errors are not merely deviations from normative grammar; they offer a unique window into the cognitive architecture of language and expose the current limitations of artificial systems that seek to replicate them. This project proposes an interdisciplinary study of linguistic errors produced by native…
Antonio Benítez-Burraco, Antonio Bova, Thomas Spalding
Over the last few decades, psycholinguistics has crucially contributed, together with neurolinguistics, to our understanding of how our brain processes language. Although languages are sensitive to their speakers' physical and social environment, the core features of language and how they are used depend primarily on…
Anna A. Ivanova, Carina Kauf, Ruimin Gao, Jingyuan Selena She + 6 more
The brain’s language network is often implicated in the representation and manipulation of abstract semantic knowledge. However, this view is inconsistent with a large body of evidence suggesting that language processing is neurally distinct from the rest of cognition. Here, we use precision brain imaging to uncover a…
Jenna Hooper, Julia Dengler, David Basilico, Matthew Nelson
Sentence comprehension requires the incremental construction of syntactic structure and semantic interpretation. Prior neural work (25) identified key neural events at major phrase boundaries during sentence comprehension. To investigate a behavioral correlation of these processes, we used self-paced reading to examine…
Samuel Kiegeland, Vésteinn Snæbjarnarson, Tim Vieira, Ryan Cotterell
Surprisal theory links human processing effort to the predictability of an upcoming linguistic unit, but empirical work often leaves the notion of a unit underspecified. In practice, experimental stimuli are segmented into linguistically motivated units (e.g., words), while pretrained language models assign probability…
Evelyn Milburn, Mila Vulchanova, Valentin Vulchanov, David Saltzman + 1 more
Multiword expressions-also called multiword chunks, fixed expressions, lexical bundles, or formulaic sequences-are familiar sequences of words that occur with high frequency in language. Recent focus on multiword expressions, as distinct units of language with distinct processing ramifications, raises the question of…
Matthew Stone, Una Stojnić
Are utterances by AI chatbots meaningful? Concretely, if a user asks, say, Anthropic's agent Claude, "What is the capital of Spain?" and Claude answers, "Madrid is the capital of Spain," does that sentence have its ordinary meaning -- and does it express a true proposition? Most ordinary users, as well as AI engineers…
Authors not listed
The materials-science literature is the richest reservoir of domain knowledge, yet converting its unstructured text—especially narrative passages and complex tables—into machine-readable data for analysis and ML model training remains challenging. To address this, we present KnowMat, an agentic, multi-stage pipeline…
Authors not listed
Agentic artificial intelligence (AI) is poised to redefine how science is conducted, automating not just data analysis but the entire research lifecycle, from hypothesis generation to validation. Yet most current AI agents remain domain-bound, tailored to specific applications such as materials synthesis or quantum…
Authors not listed
The ability to generate crystal structures directly from textual descriptions marks a pivotal advancement in materials informatics and underscores the emerging role of large language models (LLMs) in inverse design. In this work, we introduce CrysText, a text-conditioned framework that generates crystal structures in…
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Extreme weather events increasingly threaten coastal water quality, yet the mechanisms by which tropical cyclones impair microbial conditions remain poorly quantified. We develop a Large Language Model–Assisted Microbial Source Tracking (LAMST) framework to trace the origins of microbial threats—fecal indicator…