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1
Finding the best way to put media bias research into practice via an annotation app ...
Hornung, Tilman. - : Open Science Framework, 2022
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2
Are neural language models sensitive to false belief? A computational study. ...
Trott, Sean. - : Open Science Framework, 2022
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3
Similarity between person roles in a card sorting experiment ...
Maldonado, Mora. - : Open Science Framework, 2022
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4
Statistical detection of format dialects using the weighted Dowker complex ...
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5
Clustering and compatibility-based approach for large-scale group decision making with hesitant fuzzy linguistic preference relations: An application in e-waste recycling ...
Yuanyuan Zhou. - : Code Ocean, 2022
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6
Identifying the preschool home learning experiences that predict early number skills: Evidence from a longitudinal study ...
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7
Computing Entailments Online, ver. 5 ...
Dąbkowski, Maksymilian. - : Open Science Framework, 2022
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8
Computing Entailments Online, ver. 6 ...
Dąbkowski, Maksymilian. - : Open Science Framework, 2022
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9
Can distributional semantics explain performance on the false belief task? ...
Trott, Sean. - : Open Science Framework, 2022
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10
Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ...
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11
Fibrational linguistics I: first concepts ...
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12
Elastic Full Procrustes Analysis of Plane Curves via Hermitian Covariance Smoothing ...
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13
Formal Metatheory of Second-Order Abstract Syntax ...
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14
An enriched category theory of language: from syntax to semantics ...
Abstract: State of the art language models return a natural language text continuation from any piece of input text. This ability to generate coherent text extensions implies significant sophistication, including a knowledge of grammar and semantics. In this paper, we propose a mathematical framework for passing from probability distributions on extensions of given texts, such as the ones learned by today's large language models, to an enriched category containing semantic information. Roughly speaking, we model probability distributions on texts as a category enriched over the unit interval. Objects of this category are expressions in language, and hom objects are conditional probabilities that one expression is an extension of another. This category is syntactical -- it describes what goes with what. Then, via the Yoneda embedding, we pass to the enriched category of unit interval-valued copresheaves on this syntactical category. This category of enriched copresheaves is semantic -- it is where we find meaning, ... : 29 pages; v2 major revision with new proofs and computations ...
Keyword: Category Theory math.CT; Computation and Language cs.CL; FOS Computer and information sciences; FOS Mathematics
URL: https://arxiv.org/abs/2106.07890
https://dx.doi.org/10.48550/arxiv.2106.07890
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15
Complexity of optimizing over the integers ...
Basu, Amitabh. - : arXiv, 2021
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16
Composable constraints ...
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17
Boolean proportions ...
Antić, Christian. - : arXiv, 2021
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18
Development of language and the use of musical engagement as a stress coping mechanism during the COVID-19 pandemic ...
Lab, UNLV. - : Open Science Framework, 2021
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19
Grammar Equations ...
Coecke, Bob; Wang, Vincent. - : arXiv, 2021
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20
Measuring Equity Mindsets and Improvisational Practices Through Language Patterns in Equity Simulations ...
Littenberg-Tobias, Joshua. - : Open Science Framework, 2021
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