Results 91 to 100 of about 33,125 (301)
Explainable Artificial Intelligence. Second World Conference, xAI 2024. Proceedings. Part I
This four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024.
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XAI.it 2020 - Preface to the first italian workshop on explainable artificial intelligence [PDF]
, 2020 Artificial Intelligence systems are increasingly playing an increasingly important role in our daily lives. As their importance in our everyday lives grows, it is fundamental that the internal mechanisms that guide these algorithms are as clear as ...
Musto C. +3 more
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Engineering, 2020 Causal inference is a powerful modeling tool for explanatory analysis, which might enable current machine learning to become explainable. How to marry causal inference with machine learning to develop explainable artificial intelligence (XAI) algorithms ...
Kun Kuang +9 more
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Arthritis Care &Research, Accepted Article.Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed‐methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah +4 more
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Explainable Artificial Intelligence. Second World Conference, xAI 2024. Proceedings. Pt. IV
This four-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2024, held in Valletta, Malta, during July 17-19, 2024.
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Advanced Engineering Materials, EarlyView.This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
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VEGAS: Towards Visually Explainable and Grounded Artificial Social Intelligence
Social Intelligence Queries (Social-IQ) serve as the primary multimodal benchmark for evaluating a model’s social intelligence level. While impressive multiple-choice question (MCQ) accuracy is achieved by current solutions, increasing evidence shows ...
Yang, Zhengwei +4 more
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Evaluating Explainable Artificial Intelligence for X-ray Image Analysis
, 2022 The lack of justification of the results obtained by artificial intelligence (AI) algorithms has limited their usage in the medical context. To increase the explainability of the existing AI methods, explainable artificial intelligence (XAI) is proposed.
Miquel Miró-Nicolau +2 more
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Introducing Geo-Glocal Explainable Artificial Intelligence
IEEE AccessGeospatial use cases involve data with a geospatial and a temporal dimension. Machine learning is applied to such use cases for tasks such as prediction and classification.
Cedric Roussel, Klaus Bohm
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Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
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