23 papers · ranked by Valyu relevance
Jamie Reilly, Cory Shain, Valentina Borghesani, Philipp Kuhnke + 48 more
'Gabriella Vigliocco' 'Jonathan E. Peelle' 'Bradford Z. Mahon' 'Laurel J. Buxbaum' 'Asifa Majid' 'Marc Brysbaert' 'Anna M. Borghi' 'Simon De Deyne' 'Guy Dove' 'Liuba Papeo' 'Penny M. Pexman' 'David Poeppel' 'Gary Lupyan' 'Paulo Boggio' 'Gregory Hickok' 'Laura Gwilliams' 'Leonardo Fernandino' 'Daniel Mirman' 'Evangelia…
Richard Moot, Christian Retoré
This paper is a reflexion on the computability of natural language semantics. It does not contain a new model or new results in the formal semantics of natural language: it is rather a computational analysis of the logical models and algorithms currently used in natural language semantics, defined as the mapping of a…
Jona Sassenhagen, Christian J. Fiebach
How is semantic information stored in the human mind and brain? Some philosophers and cognitive scientists argue for vectorial representations of concepts, where the meaning of a word is represented as its position in a high-dimensional neural state space. At the intersection of natural language processing and…
Kun Xing
Formal Semantics and Distributional Semantics are two important semantic frameworks in Natural Language Processing (NLP). Cognitive Semantics belongs to the movement of Cognitive Linguistics, which is based on contemporary cognitive science. Each framework could deal with some meaning phenomena, but none of them…
Gemma Boleda
Distributional semantics provides multi-dimensional, graded, empirically induced word representations that successfully capture many aspects of meaning in natural languages, as shown in a large body of work in computational linguistics; yet, its impact in theoretical linguistics has so far been limited. This review…
Qianwen Chang, Elizabeth Jefferies, Rebecca L. Jackson
The relationship between semantics and syntax is highly contested. Neuroimaging evidence has offered conflicting views on whether these domains are neurally separable, in part because prior work has not distinguished two key components of semantic cognition: semantic representation and semantic control. In this study…
Vladimír Havlík
Can a machine understand the meanings of natural language? Recent developments in the generative large language models (LLMs) of artificial intelligence have led to the belief that traditional philosophical assumptions about machine understanding of language need to be revised. This article critically evaluates the…
Andrea Bruera, Gesa Hartwigsen
Non-invasive brain stimulation (NIBS) studies on semantic cognition hold the promise of revealing the functional relevance of brain areas through causal intervention. A primary challenge, however, is that findings are often interpreted through binary distinctions between sets of stimuli (e.g. related/unrelated words…
Sarah A. Fisher
According to some philosophers, a sentence's semantics can fail to constitute a complete propositional content, imposing mere constraints on such a content. Recently, Daniel Harris has begun developing a formal constraint semantics. He claims that the semantic values of sentences constrain what speakers can literally…
Sina Ahmadi
Dictionaries are fundamental resources for people to learn and document languages as well as for computers to process natural languages. A dictionary provides a finegrained structure and description of the vocabulary of a language. With decades of advances in electronic lexicography, a significant amount of…
Voula Giouli
Multiword expressions (MWEs) are sequences of words that pose a challenge to the computational processing of human languages due to their idiosyncrasies and the mismatch between their phrasal structure and their semantics. These idiosyncrasies are of lexical, morphosyntactic and semantic 11 nature, namely…
Alona Fyshe, Gustavo Sudre, Leila Wehbe, Nicole Rafidi + 1 more
As a person reads, the brain performs complex operations to create higher order semantic representations from individual words. While these steps are effortless for competent readers, we are only beginning to understand how the brain performs these actions. Here, we explore semantic composition using…
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…
Leonardo Fernandino, Lisa L. Conant
The organization of semantic memory, including memory for word meanings, has long been a central question in cognitive science. Although there is general agreement that lexical semantic representations must make contact with sensory-motor and affective experiences in a non-arbitrary fashion, the nature of this…
Elberto A. Plazas
The stimulus equivalence (SE) paradigm has become a central explanatory framework for language and complex symbolic behavior within behavior analysis. Its explanatory power rests on three core assumptions: (1) human symbolic behavior is grounded in the semantic relation between words and their referents; (2) this…
Brady Clark
Work within the minimalist program attempts to meet the criterion of evolvability: “any mechanisms and primitives ascribed to UG rather than derived from independent factors must plausibly have emerged in what appears to have been a unique and relatively sudden event on the evolutionary timescale” (Chomsky et al.…
Matthijs Westera, Gemma Boleda
Distributional semantics has had enormous empirical success in Computational Linguistics and Cognitive Science in modeling various semantic phenomena, such as semantic similarity, and distributional models are widely used in state-of-the-art Natural Language Processing systems. However, the theoretical status of…
Robyn Carston
First, the wide applicability of the relevance-theoretic pragmatic account of how new (ad hoc) senses of words and new (ad hoc) words arise spontaneously in communication/comprehension is demonstrated. The lexical pragmatic processes of meaning modulation and metonymy are shown to apply equally to simple words, noun to…
Miloje Rakočević
In some previous works (2018a,b; 2019, 2021a,b, 2022) we presented a new type of mirror symmetry, expressed in the set of protein amino acids; such a symmetry, that it simultaneously represents the semiotic essence of the genetic code. In this paper we provide new evidences that the genetic code represents the unity of…
Noel O'Boyle, Andrew Dalke
Background There has been increasing interest in the use of deep neural networks for de novo design of molecules with desired properties. A common approach is to train a generative model on SMILES strings and then use this to generate SMILES strings for molecules with a desired property. Unfortunately, these SMILES…
Richard Apodaca
Despite its widespread use, Simplified Molecular Input Line Entry System (SMILES) remains underspecified. The lack of a detailed specification encourages improvisation by software developers, complicates data standardization efforts, and undermines extension development. Balsa, a reformulation of SMILES, addresses…
Philip Strömert, Johannes Hunold, Stuart Chalk, Leah McEwen + 1 more
This whitepaper aims to provide guidance to improve standardization and quality of ontologies development and curation concerning term definitions. We outline an approach on how definitions of The IUPAC Compendium of Chemical Terminology (colloquially known as the "Gold Book") could be applied as a definition source…
Pieter Floris Jacobs, Robert Pollice
Scientists across domains are often challenged to master domain-specific languages (DSLs) for their research, which are merely a means to an end but are pervasive in fields like computational chemistry. Automated code generation promises to overcome this barrier, allowing researchers to focus on their core expertise.…