Accountable and Explainable Methods for Complex Reasoning over Text

This thesis presents research that expands the collective knowledge in the areas of accountability and transparency of machine learning (ML) models developed for complex reasoning tasks over text. In particular, the presented results facilitate the analysis of the reasons behind the outputs of ML mo...

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Dades bibliogràfiques

Autor principal:	Atanasova, Pepa (Autor)
Autor corporatiu:	SpringerLink (Online service)
Format:	Electrònic eBook
Idioma:	anglès
Publicat:	Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edició:	1st ed. 2024.
Matèries:	Natural language processing (Computer science). Information storage and retrieval systems. Machine learning. Natural Language Processing (NLP). Information Storage and Retrieval. Machine Learning.
Accés en línia:	https://doi.org/10.1007/978-3-031-51518-7
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