Search · four archives
Search · four archives
25 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…
Michela Assale, Linda Greta Dui, Andrea Cina, Andrea Seveso + 1 more
'Federico Cabitza'] Problem: Clinical practice requires the production of a time- and resource-consuming great amount of notes. They contain relevant information, but their secondary use is almost impossible, due to their unstructured nature. Researchers are trying to address this problems, with traditional and…
Georgiana Tucudean, Marian Bucos, Bogdan Dragulescu, Catalin Daniel Caleanu + 1 more
'Catalin Daniel Caleanu' 'Maria Navarro-Caceres'] Natural language processing (NLP) tasks can be addressed with several deep learning architectures, and many different approaches have proven to be efficient. This study aims to briefly summarize the use cases for NLP tasks along with the main architectures. This…
Daniel W. Otter, Julian Richard Medina, Jugal Kalita
—Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This survey provides a brief introduction to the field and a quick overview of deep learning architectures and methods. It then sifts through the plethora of recent…
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…
Flavio Massimiliano Cecchini, Elisabetta Fersini
We begin by introducing the Computer Science branch of Natural Language Processing, then narrowing the attention on its subbranch of Information Extraction and particularly on Named Entity Recognition, discussing briefly its main methodological approaches. It follows an introduction to state-of-the-art Conditional…
Joshua Conrad Jackson, Joseph Watts, Johann-Mattis List, Curtis Puryear + 2 more
'Curtis Puryear' 'Ryan Drabble' 'Kristen A. Lindquist'] Humans have been using language for millennia but have only just begun to scratch the surface of what natural language can reveal about the mind. Here we propose that language offers a unique window into psychology. After briefly summarizing the legacy of language…
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…
Akshansh Mishra, Vijaykumar S. Jatti, Vaishnavi More, Anish Dasgupta + 2 more
'Devarrishi Dixit' 'Eyob Messele Sefene'] Abstract: The ability to interpret spoken language is connected to natural language processing. It involves teaching the AI how words relate to one another, how they are meant to be used, and in what settings. The goal of natural language processing (NLP) is to get a machine…
Guido M. Linders, Max M. Louwerse
Most natural language models and tools are restricted to one language, typically English. For researchers in the behavioral sciences investigating languages other than English, and for those researchers who would like to make cross-linguistic comparisons, hardly any computational linguistic tools exist, particularly…
U. Reshma, H B Barathi Ganesh, Mandar Kale, Prachi Mankame + 1 more
'Gouri Kulkarni'] In today's scenario, imagining a world without negativity is something very unrealistic, as bad NEWS spreads more virally than good ones. Though it seems impractical in real life, this could be implemented by building a system using Machine Learning and Natural Language Processing techniques in…
Sreejan Kumar, Theodore R. Sumers, Takateru Yamakoshi, Ariel Goldstein + 5 more
Humans use complex linguistic structures to transmit ideas to one another. The brain is thought to deploy specialized computations to process these structures. Recently, a new class of artificial neural networks based on the Transformer architecture has revolutionized the field of language modeling, attracting…
Reto Gubelmann
Taking Leibniz' ideal of a universal truth-calculating machine as a vantage point, this article provides a philosophically sound analysis of the concept of reasoning in NLP. It argues that reasoning always involves inference, which in turn requires being guided by reason relations. Based on this, the article argues…
Alessandro Lopopolo, Milena Rabovsky
Recent research has shown that the internal dynamics of an artificial neural network model of sentence comprehension displayed a similar pattern to the amplitude of the N400 in several conditions known to modulate this event-related potential. These results led 63 to suggest that the N400 might reflect change in an…
Dario Borrelli, Gabriela Gongora Svartzman, Carlo Lipizzi, Christopher M. Danforth
'Christopher M. Danforth'] Symbolic sequential data are produced in huge quantities in numerous contexts, such as text and speech data, biometrics, genomics, financial market indexes, music sheets, and online social media posts. In this paper, an unsupervised approach for the chunking of idiomatic units of sequential…
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…
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…
Sharmistha Jat, Erika J C Laing, Partha Talukdar, Tom Mitchell
The human brain is very effective at integrating new words one by one into the composed representation of a sentence as it is read left-to-right. This raises the important question of what happens to the neural representations of words present earlier in the sentence? For example, do the strength of word…
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…
Michael P. Broderick, Andrew J. Anderson, Giovanni M. Di Liberto, Michael J. Crosse + 1 more
Understanding natural speech requires that the human brain convert complex spectrotemporal patterns of acoustic input into meaning in a rapid manner that is reasonably tightly time-locked to the incoming speech signal. However, neural evidence for such a time-locked process has been lacking. Here, we sought such…
Sophie Jano, Zachariah Cross, Alex Chatburn, Matthias Schlesewsky + 1 more
The extent to which the brain predicts upcoming information during language processing remains controversial. To shed light on this debate, the present study reanalysed Nieuwland and colleagues’ (2018) replication of 21. Participants (N = 356) viewed sentences containing articles and nouns of varying predictability…
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…
Qianxiang Ai, Fanwang Meng, Jiale Shi, Brenden Pelkie + 1 more
The popularity of data-driven approaches and machine learning (ML) techniques in the field of organic chemistry and its various subfields has increased the value of structured reaction data. Most data in chemistry is represented by unstructured text, and due to the vastness of the organic chemistry literature (papers…
Authors not listed
The interdisciplinary nature of redox flow batteries (RFBs), spanning chemistry, materials, and engineering, has led to a vast and fragmented body of research, hindering the efficient synthesis of knowledge. An intelligent question-answering system is there-fore essential to organize this dispersed knowledge, enhance…
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…