Titlebook: Explainable Artificial Intelligence; First World Conferen Luca Longo Conference proceedings 2023 The Editor(s) (if applicable) and The Auth

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書目名稱Explainable Artificial Intelligence影響因子(影響力)




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書目名稱Explainable Artificial Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Explainable Artificial Intelligence被引頻次




書目名稱Explainable Artificial Intelligence被引頻次學(xué)科排名




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書目名稱Explainable Artificial Intelligence年度引用學(xué)科排名




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書目名稱Explainable Artificial Intelligence讀者反饋學(xué)科排名

squander

Evaluating Self-attention Interpretability Through Human-Grounded Experimental Protocolntly better than a random baseline regarding average participant reaction time and accuracy. Moreover, data analysis highlights that high probability prediction induces great explanation relevance. This work shows how self-attention can be aggregated and used to explain Transformer classifiers. The

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Causal-Based Spatio-Temporal Graph Neural Networks for?Industrial Internet of?Things Multivariate Tidata features effectively. Experimental results on industrial datasets demonstrate that the proposed method outperforms existing baselines and achieves state-of-the-art performance. The proposed approach offers a promising solution for accurate and interpretable spatio-temporal data forecasting.

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Development of?a?Human-Centred Psychometric Test for?the?Evaluation of?Explanations Produced by?XAI ability. The questionnaire development process was divided into two phases. First, a pilot study was designed and carried out to test the first version of the questionnaire. The results of this study were exploited to create a second, refined version of the questionnaire. The questionnaire was evalu