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In this paper, we introduce a novel approach for semantic description of object features based on the prototypicality effects of the Prototype Theory. Our prototype-based description model encodes and stores the semantic meaning of an…

Computer Vision and Pattern Recognition · Computer Science 2021-07-08 Omar Vidal Pino , Erickson Rangel Nascimento , Mario Fernando Montenegro Campos

Ontological models are attempts to quantitatively describe the results of a probabilistic theory, such as Quantum Mechanics, in a framework exhibiting an explicit realism-based underpinning. Unlike either the well known quasi-probability…

Quantum Physics · Physics 2008-07-02 Nicholas Harrigan , Terry Rudolph , Scott Aaronson

In the concluding remarks of Ontological Promiscuity Hobbs (1985) made what we believe to be a very insightful observation: given that semantics is an attempt at specifying the relation between language and the world, if "one can assume a…

Computation and Language · Computer Science 2019-04-16 Walid S. Saba

Comparative constructions pose a challenge in Natural Language Inference (NLI), which is the task of determining whether a text entails a hypothesis. Comparatives are structurally complex in that they interact with other linguistic…

Computation and Language · Computer Science 2020-05-19 Izumi Haruta , Koji Mineshima , Daisuke Bekki

We firstly show that the standard interpretation of natural quantification in mathematical logic does not provide a satisfying account of its original richness. In particular, it ignores the difference between generic and distributive…

Logic · Mathematics 2011-07-12 Michele Abrusci , Christian Retoré

The study of homotopy theoretic phenomena in the language of type theory is sometimes loosely called `synthetic homotopy theory'. Homotopy theory in type theory is only one of the many aspects of homotopy type theory, which also includes…

Logic · Mathematics 2019-06-25 Egbert Rijke

Preferences of individuals are distributions of elements generated by generalized functions. Models of economic decision-making derived from such distributions are consistent with results of physiological experiments, and explain any…

Neurons and Cognition · Quantitative Biology 2012-01-20 Leonid A. Shapiro

Building on research arguing for the possibility of conceptual and categorical knowledge acquisition through statistics contained in language, we evaluate predictive language models (LMs) -- informed solely by textual input -- on a…

Computation and Language · Computer Science 2021-05-10 Kanishka Misra , Allyson Ettinger , Julia Taylor Rayz

Superlatives are used to single out elements with a maximal/minimal property. Semantically, superlatives perform a set comparison: something (or some things) has the min/max property out of a set. As such, superlatives provide an ideal…

Computation and Language · Computer Science 2024-10-18 Valentina Pyatkin , Bonnie Webber , Ido Dagan , Reut Tsarfaty

Semantic composition remains an open problem for vector space models of semantics. In this paper, we explain how the probabilistic graphical model used in the framework of Functional Distributional Semantics can be interpreted as a…

Computation and Language · Computer Science 2017-09-04 Guy Emerson , Ann Copestake

This paper presents a partial solution to a component of the problem of lexical choice: choosing the synonym most typical, or expected, in context. We apply a new statistical approach to representing the context of a word through lexical…

Computation and Language · Computer Science 2007-05-23 Philip Edmonds

We present a novel semantic framework for modeling linguistic expressions of generalization---generic, habitual, and episodic statements---as combinations of simple, real-valued referential properties of predicates and their arguments. We…

Computation and Language · Computer Science 2026-04-17 Venkata Subrahmanyan Govindarajan , Benjamin Van Durme , Aaron Steven White

Inspired by empirical work in neuroscience for Bayesian approaches to brain function, we give a unified probabilistic account of various types of symbolic reasoning from data. We characterise them in terms of formal logic using the…

Artificial Intelligence · Computer Science 2026-02-24 Hiroyuki Kido

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…

Computation and Language · Computer Science 2016-05-16 Richard Moot , Christian Retoré

Many real systems have been modelled in terms of network concepts, and written texts are a particular example of information networks. In recent years, the use of network methods to analyze language has allowed the discovery of several…

Computation and Language · Computer Science 2016-06-28 Henrique F. de Arruda , Luciano da F. Costa , Diego R. Amancio

In this paper we argue for a paradigmatic shift from `reductionism' to `togetherness'. In particular, we show how interaction between systems in quantum theory naturally carries over to modelling how word meanings interact in natural…

Computation and Language · Computer Science 2016-02-25 Bob Coecke

Compositionality is thought to be a key component of language, and various compositional benchmarks have been developed to empirically probe the compositional generalization of existing sequence processing models. These benchmarks often…

Machine Learning · Computer Science 2024-05-07 Parikshit Ram , Tim Klinger , Alexander G. Gray

A notion of morphism that is suitable for the sheaf-theoretic approach to contextuality is developed, resulting in a resource theory for contextuality. The key features involve using an underlying relation rather than a function between…

Quantum Physics · Physics 2019-01-30 Martti Karvonen

This paper investigates the possibility of performing automated reasoning in probabilistic logic when probabilities are expressed by means of linguistic quantifiers. Each linguistic term is expressed as a prescribed interval of proportions.…

Artificial Intelligence · Computer Science 2013-03-25 Didier Dubois , Henri Prade , Lluis Godo , Ramon Lopez de Mantaras

Neural Processes (NPs) are appealing due to their ability to perform fast adaptation based on a context set. This set is encoded by a latent variable, which is often assumed to follow a simple distribution. However, in real-word settings,…

Machine Learning · Computer Science 2023-06-28 Dharmesh Tailor , Mohammad Emtiyaz Khan , Eric Nalisnick
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