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A gentle introduction to Girard's Transcendental Syntax for the linear logician
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In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2022 (2022)
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cushLEPOR uses LABSE distilled knowledge to improve correlation with human translation evaluations
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In: Erofeev, Gleb, Sorokina, Irina, Han, Lifeng orcid:0000-0002-3221-2185 and Gladkoff, Serge (2021) cushLEPOR uses LABSE distilled knowledge to improve correlation with human translation evaluations. In: Machine Translation Summit 2021, 16-20 Aug 2021, USA (online). (In Press) (2021)
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Meta-evaluation of machine translation evaluation methods
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In: Han, Lifeng orcid:0000-0002-3221-2185 (2021) Meta-evaluation of machine translation evaluation methods. In: Workshop on Informetric and Scientometric Research (SIG-MET), 23-24 Oct 2021, Online. (2021)
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| 5 |
Salience Estimation and Faithful Generation: Modeling Methods for Text Summarization and Generation
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| 6 |
Multiplicative Linear Logic from Logic Programs and Tilings
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In: https://hal.archives-ouvertes.fr/hal-02895111 ; 2021 (2021)
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| 7 |
A gentle introduction to Girard's Transcendental Syntax for the linear logician
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In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021)
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| 8 |
Stellar Resolution: Multiplicatives - for the linear logician, through examples
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In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021)
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| 9 |
A gentle introduction to Girard's Transcendental Syntax for the linear logician
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In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021)
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| 10 |
Stellar Resolution: Multiplicatives - for the linear logician, through examples
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In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021)
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| 11 |
Quantifying Holistic Capacity Response and Healthcare Resilience in Tackling COVID-19: Assessment of Country Capacity by MCDM ...
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| 12 |
Quantifying Holistic Capacity Response and Healthcare Resilience in Tackling COVID-19: Assessment of Country Capacity by MCDM ...
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| 13 |
Quantifying Holistic Capacity Response and Healthcare Resilience in Tackling COVID-19: Assessment of Country Capacity by MCDM.xlsx ...
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| 15 |
Modelling Artificial Intelligence in Economics
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Abstract:
Economists' two main theoretical approaches to understanding Artificial Intelligence (AI) impacts have been the task-approach to labor markets and endogenous growth theory. Therefore, the recent integration of the task-approach into an endogenous growth model by Acemoglu and Restrepo (AR) is a useful advance. However, it is subject to the shortcoming that it does not explicitly model AI and its technological feasibility. The AR model focuses on tasks and skills but not on abilities, while abilities better characterize AI services' nature. This paper addresses this shortcoming by elaborating the task-approach with AI abilities for use within endogenous growth models. This more ability-sensitive specification of the task-approach allows for more nuanced and realistic impacts of progress in artificial intelligence (AI) on the economy to be captured.
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Keyword:
Artificial Intelligence; ddc:330; E21; E25; endogenous growth theory; J24; labor economics; mathematical models; O33; O47
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URL: http://hdl.handle.net/10419/232923
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| 16 |
Transforming the study of organisms: Phenomic data models and knowledge bases.
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In: PLoS computational biology, vol 16, iss 11 (2020)
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| 17 |
Choice of mathematic models of soils in static and seismic analyses of embankment dams
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In: Structural Mechanics of Engineering Constructions and Buildings, Vol 16, Iss 4, Pp 261-270 (2020) (2020)
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| 18 |
The software part, the fundamental and organizational structure of the software and hardware complex to ensure the safety of hydraulic and hydropower structures under the construction
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In: Structural Mechanics of Engineering Constructions and Buildings, Vol 16, Iss 6, Pp 465-471 (2020) (2020)
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| 19 |
Co-constructing Peer Feedback Practices in an Elementary School Mathematics Classroom: An Enactivist Perspective
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Interaction matrix selection in spatial econometrics with an application to growth theory
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In: ISSN: 0166-0462 ; Regional Science and Urban Economics ; https://halshs.archives-ouvertes.fr/halshs-01278545 ; Regional Science and Urban Economics, Elsevier, 2019, 75, pp.49-69. ⟨10.1016/j.regsciurbeco.2019.01.002⟩ (2019)
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