26 papers · ranked by Valyu relevance
Diksha Khurana, Aditya Koli, Kiran Khatter, Sukhdev Singh
Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. The paper…
Andrea E. Martin
I argue that cue integration, a psychophysiological mechanism from vision and multisensory perception, offers a computational linking hypothesis between psycholinguistic theory and neurobiological models of language. I propose that this mechanism, which incorporates probabilistic estimates of a cue's reliability, might…
Zoha Deldar, Carlos Gevers-Montoro, Ali Khatibi, Ladan Ghazi-Saidi
Language processing involves other cognitive domains, including Working Memory (WM). Much detail about the neural correlates of language and WM interaction remains unclear. This review summarizes the evidence for the interaction between WM and language obtained via functional Magnetic Resonance Imaging (fMRI) in the…
Evelina Fedorenko
What role does domain-general cognitive control play in understanding linguistic input? Although much evidence has suggested that domain-general cognitive control and working memory resources are sometimes recruited during language comprehension, many aspects of this relationship remain elusive. For example, how…
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…
Evelina Fedorenko, Zachary Mineroff, Matthew Siegelman, Idan Blank
To understand what you are reading now, your mind retrieves the meanings of words from a linguistic knowledge store (lexico-semantic processing) and identifies the relationships among them to construct a complex meaning (syntactic or combinatorial processing). Do these two sets of processes rely on distinct…
Shaonan Wang, Nai Ding, Nan Lin, Jiajun Zhang + 1 more
Language understanding is a key scientific issue in the fields of cognitive and computer science. However, the two disciplines differ substantially in the specific research questions. Cognitive science focuses on analyzing the specific mechanism of the brain and investigating the brain's response to language; few…
Philippe Blache
Most architectures and models of language processing have been built upon a restricted view of language, which is limited to sentence processing. These approaches fail to capture one primordial characteristic: efficiency. Many facilitation effects are known to be at play in natural situations such as conversation…
Kevin Mote
| | | INTRODUCTION: "WHY CAN'T COMPUTERS UNDERSTAND PLAIN ENGLISH?" 1 | | --- | --- | --- | | 1. | THE PURPOSE: | 3 | | 1.1 | | FOUNDATION: "THE HUMAN BRAIN AND COGNITIVE LINGUISTICS" 6 | | 1.2 | | METHODOLOGY: " THE GREAT DEBATE: RULES OR STATISTICS " 9 | | | 1.2.1 | The Rationalists: RULES 10 | | | 1.2.2 | The…
E. Roger, L. Rodrigues De Almeida, H. Lœvenbruck, M. Perrone-Bertolotti + 8 more
Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed…
Sarah Aliko, Melissa Franch, Viktor Kewenig, Bangjie Wang + 5 more
Models of the neurobiology of language suggest that a small number of anatomically fixed brain regions are responsible for language functioning. This derives from centuries of aphasia studies and decades of neuroimaging. The latter rely on thresholded measures of central tendency applied to activity patterns from…
Daniel Gildea, T. Florian Jaeger
Most languages use the relative order between words to encode meaning relations. Languages differ, however, in what orders they use and how these orders are mapped onto different meanings. We test the hypothesis that –despite these differences– human languages might constitute different 'solutions' to common pressures…
Saima Malik-Moraleda, Maya Taliaferro, Steve Shannon, Niharika Jhingan + 8 more
What constitutes a language? Natural languages share features with other domains: from math, to music, to gesture. However, the brain mechanisms that process linguistic input are highly specialized, showing little response to diverse non-linguistic tasks. Here, we examine constructed languages (conlangs) to ask whether…
Antonio Benítez-Burraco
Linguistics needs to embrace all the way down a key feature of language: its diversity. In this paper, we build on recent experimental findings and theoretical discussions about the neuroscience and the cognitive science of linguistic variation, but also on proposals by theoretical biology, to advance some future…
Pablo Contreras Kallens, Morten H. Christiansen
Traditional accounts of language postulate two basic components: words stored in a lexicon, and rules that govern how they can be combined into meaningful sentences, a grammar. But, although this words-and-rules framework has proven itself to be useful in natural language processing and cognitive science, it has also…
Authors not listed
Natural language processing with the help of large language models such as ChatGPT has become ubiquitous in many software applications and allows users to interact even with complex hardware or software in an intuitive way. The recent concepts of Self-Driving Labs and Material Acceleration Platforms stand to benefit…
Mike A. Sharwood Smith
The focus of the current topic is the analysis and interpretation of second language (L2) and multilingual data. Looking at data from speakers who have learned their additional languages after the mother tongue has become well established is of special interest. It advances our knowledge about how different language…
Nicolas Stefaniak, Stéphanie Caillies, Ferenc Kemény
It is becoming increasingly clear that language at least partially depends on learning and memory processes, which have been conceptualized somewhat differently according to areas of research. Automatic processes have often been thought of in terms of statistical learning, implicit learning, or procedural learning and…
Authors not listed
Step-by-step thinking is essential in all domains of chemical sciences and engineering. While machine learning tools are broadly used, algorithms that automate reasoning are far less common. We elaborate on seven categories of human reasoning activities and connect each to applications in chemical science and…
Authors not listed
In recent years, the development of large language models (LLMs) has revolutionized various fields of natural science, yet their application in molecular data processing remains constrained due to the reliance on single-modality inputs and outputs. To bridge the gap between experimenters and computational tools, we…
Zhichu Ren, Zhen Zhang, Yunsheng Tian, Ju Li
Autonomous laboratories were previously controlled mainly by scripting languages such as Python, limiting their usage among experimentalists. The recent release of OpenAI's ChatGPT API's function calling feature has enabled seamless integration and execution of Python subroutines in experimental workflows using voice…
Shimon Edelman
What does it mean to know language? Since the Chomskian revolution, one popular answer to this question has been: to possess a generative grammar that exclusively licenses certain syntactic structures. Decades later, not even an approximation to such a grammar, for any language, has been formulated; the idea that…
Authors not listed
The exponentially growing body of scientific literature has made manual synthesis and hypothesis generation increasingly impractical, introducing an essential bottleneck in the scientific discovery pipeline. While large language models (LLMs) have unprecedented capability to process and summarize textual knowledge…
Julian Ivanov, Alan Lipkus, Haitao Chen, Chris Aultman + 3 more
A novel bibliometric methodology based on natural language data processing for identifying emerging topics in science is presented. Along with the usual practice of data collection and preprocessing, our method includes a natural language processing (NLP) technique and an innovative mathematical function data…
Authors not listed
Bioprocess engineering has incorporated effective AI applications in recent years that consist of traditional approaches to training models on relevant data to then analyze and predict new and unseen data. The missing component has been the ability to process mixed data from an assortment of dissimilar information…
Authors not listed
The scarcity and expense of fatigue data limits optimal design of components and constrains companies to a few well qualified materials when safety-critical applications are concerned. This research investigates different strategies to improve extraction of structured information from unstructured scientific…