Search · four archives
Search · four archives
20 papers · ranked by Valyu relevance
Behrooz Mansouri
This paper presents a survey of Abstract Meaning Representation (AMR), a semantic representation framework that captures the meaning of sentences through a graph-based structure. AMR represents sentences as rooted, directed acyclic graphs, where nodes correspond to concepts and edges denote relationships, effectively…
Daniel Kaiser, Arthur M. Jacobs, Radoslaw M. Cichy
conceptual representations are critical for human cognition. Despite their importance, key properties of these representations remain poorly understood. Here, we used computational models of distributional semantics to predict multivariate fMRI activity patterns during the activation and contextualization of abstract…
Raymond Turner, Neal G. Anderson
Representation and abstraction are two of the fundamental concepts of computer science. Together they enable “high-level” programming: without abstraction programming would be tied to machine code; without a machine representation, it would be a pure mathematical exercise. Representation begins with an abstract…
Barbara Kaup, Rolf Ulrich, Karin M. Bausenhart, Donna Bryce + 17 more
'Martin V. Butz' 'David Dignath' 'Carolin Dudschig' 'Volker H. Franz' 'Claudia Friedrich' 'Caterina Gawrilow' 'Jürgen Heller' 'Markus Huff' 'Mandy Hütter' 'Markus Janczyk' 'Hartmut Leuthold' 'Hanspeter Mallot' 'Hans-Christoph Nürk' 'Michael Ramscar' 'Nadia Said' 'Jennifer Svaldi' 'Hong Yu Wong'] Accounting for how the…
Daniel Alcalá-López, David Soto
The present functional MRI study addressed how the brain maps different aspects of social information. We focused on two key dimensions of social knowledge: affect and likableness. Thirty participants were presented with audio definitions, half referring to affective (e.g. empathetic) and half to non-affective concepts…
Dounia Lakhzoum, Marie Izaute, Ludovic Ferrand, Kristof Strijkers
Over the last decade, hypotheses ranging from linguistic symbol processing to embodiment have been formulated to account for the content and mechanisms responsible for the representation of abstract concepts. Results of recent studies have suggested that abstract concepts, just like concrete ones, can benefit from…
Ana G. Chavez, Xinyuan Yan, Melissa Franch, Elizabeth A. Mickiewicz + 28 more
We utilize internal representations of meaning for two purposes: to understand the words we hear and to generate our own speech. This dual requirement necessitates abstract, modality-agnostic representations. Building on work identifying it as a hub for relational mapping, we hypothesized that the hippocampus supports…
Bryan Min, Sangho Suh, Jim Hollan, Haijun Xia
The principle of abstraction guides the design of interactive systems, yet we lack a conceptual framework to understand how it shapes interaction design. Existing models, such as the gulfs of execution and evaluation, do not explicitly model abstractions in the system or in users' mental models, and therefore lack…
Robert M. Mok, Bradley C. Love
For decades, researchers have debated whether mental representations are symbolic or grounded in sensory inputs and motor programs. Certainly, aspects of mental representations are grounded. However, does the brain also contain abstract concept representations that mediate between perception and action in a flexible…
Anna M. Borghi, Olga Capirci, Gabriele Gianfreda, Virginia Volterra
One of the most important challenges for embodied and grounded theories of cognition concerns the representation of abstract concepts, such as “freedom.” Many embodied theories of abstract concepts have been proposed. Some proposals stress the similarities between concrete and abstract concepts showing that they are…
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…
Hai Zhuge
Summarization is one of the key features of human intelligence. It plays an important role in understanding and representation. With rapid and continual expansion of texts, pictures and videos in cyberspace, automatic summarization becomes more and more desirable. Text summarization has been studied for over half…
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…
Akira Utsumi
How are abstract concepts grounded in perceptual experiences for shaping human conceptual knowledge? Recent studies on abstract concepts emphasizing the role of language have argued that abstract concepts are grounded indirectly in perceptual experiences and language (or words) functions as a bridge between abstract…
Briony Banks, Anna M. Borghi, Raphaël Fargier, Chiara Fini + 5 more
concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological…
Eloy Parra-Barrero, Yulia Sandamirskaya
Representation is a key notion in neuroscience and artificial intelligence (AI). However, a longstanding philosophical debate highlights that specifying what counts as representation is trickier than it seems. With this brief opinion paper we would like to bring the philosophical problem of representation into…
Haizi Yu, Igor Mineyev, Lav R. Varshney
Abstraction plays a key role in concept learning and knowledge discovery; this paper is concerned with computational abstraction. In particular, we study the nature of abstraction through a group-theoretic approach, formalizing it as symmetry-driven—as opposed to data-driven—hierarchical clustering. Thus, the resulting…
Davide Nunes, Luís Antunes
One goal of Artificial Intelligence is to learn meaningful representations for natural language expressions, but what this entails is not always clear. A variety of new linguistic behaviours present themselves embodied as computers, enhanced humans, and collectives with various kinds of integration and communication.…
Authors not listed
Machine learning is increasingly used to predict reaction properties such as barrier heights, reaction energies, rates, or yields, as well as the underlying molecular geometries, including transition state structures. While such predictions have the potential to provide mechanistic insight for high-impact applications…
Gregory Kell, Ryan‐Rhys Griffiths, Anthony Bourached, David G. Stork
We present a novel bi-modal system based on deep networks to address the problem of learning associations and simple meanings of objects depicted in "authored" images, such as fine art paintings and drawings. Our overall system processes both the images and associated texts in order to learn associations between images…